BibTeX
BibTeX
201. Kolmanovsky, I., Cunis, T., & Garone, E. (2024, January). Command Governors Based on Bilevel Optimization for Constrained Spacecraft Orbital Transfer.
AIAA SCITECH 2024 Forum.
https://doi.org/10.2514/6.2024-0097
BibTeX
200. Cunis, T., & Kolmanovsky, I. (2024). Input-to-State Stability of Newton Methods for Generalized Equations in Nonlinear Optimization⋆.
2024 IEEE 63rd Conference on Decision and Control (CDC), 5950–5956.
https://doi.org/10.1109/CDC56724.2024.10885904
Abstract
We show that Newton methods for generalized equations are input-to-state stable with respect to perturbations such as due to inexact computations. We then use this result to obtain convergence and robustness of a multistep Newton-type method for multivariate generalized equations. We demonstrate the usefulness of the results with other applications to nonlinear optimization. In particular, we provide a new proof for (robust) local convergence of the augmented Lagrangian method.BibTeX
BibTeX
198. Özkurt, S., Burkhardt, T., Schimpf, F., & Fichter, W. (2023, May). The Impact of Control Augmentation and Stability Augmentation System Parameters on Kinetosis of Helicopter Passengers. Proceedings of the 79th Annual Forum of the Vertical Flight Society.
BibTeX
197. Özkurt, S., Burkhardt, T., Schimpf, F., & Fichter, W. (2023, May). The Impact of Control Augmentation and Stability Augmentation System Parameters on Kinetosis of Rotorcraft Passengers.
Proceedings of the 79th Annual Forum of the Vertical Flight Society.
https://doi.org/10.4050/F-0079-2023-18076
BibTeX
196. Rothaupt, B., Spülbeck, M., & Fichter, W. (2023, May). Simulator-Based Evaluation of Visual Pilot Assistance for Coaxial Ultralight Helicopters.
Proceedings of the Vertical Flight Society 79th Annual Forum.
https://doi.org/10.4050/f-0079-2023-18029
Abstract
This paper presents a flight simulator study that examines whether a display inside the cockpit can aid helicopter pilots with little to no experience in completing basic maneuvers. The study participants have no prior experience as helicopter pilots. The flight simulation uses a dynamic model of a coaxial ultralight helicopter horizontal motion that includes a stability augmentation system. A virtual reality headset is used to give the participants a realistic sense of perspective. The benchmark task includes decelerating into hover and hovering above a target for a given time. Three cueing configurations are compared. One includes visual cues on the ground that mark the hover target position. The two others add either a heads down display or a heads up display inside the cockpit, which visualize the relative target position and a prediction of the helicopter motion. With the proposed displays available inside the cockpit, participants tend to reach the target faster and more consistently. Hover performance is not improved by an additional display as the pilots mostly rely on visual cues on the ground during hover. In summary, both log data and pilot feedback suggest that the proposed displays are primarily beneficial in flight phases where the helicopter moves.BibTeX
195. Heni, N., Rothaupt, B., & Fichter, W. (2023, May). Modeling of Helicopter Pilot Behavior through Methods of Artificial Intelligence.
Proceedings of the Vertical Flight Society 79th Annual Forum.
https://doi.org/10.4050/f-0079-2023-18081
Abstract
Machine Learning algorithms are used in this paper to synthesize models for an ultralight coaxial helicopter pilot controlling the roll- and pitch motion during stationary hover. Different topologies of neural networks modeling the pilot are evolved with a neuroevolutionary algorithm, and trained via a data-driven approach using datasets that are collected from both real hover sequences and piloted flight simulations. The models are validated using flight test data and evaluated in a closed loop simulation alongside helicopter and turbulence models. Results demonstrate the models capability to stabilize the helicopter during hover and thus, to imitate human pilot behavior.BibTeX
Abstract
Numerous interesting properties in nonlinear systems analysis can be written as polynomial optimization problems with nonconvex sum-of-squares problems. To solve those problems efficiently, we propose a sequential approach of local linearizations leading to tractable, convex sum-of-squares problems. Local convergence is proven under the assumption of strong regularity and the new approach is applied to estimate the region of attraction of a polynomial aircraft model.BibTeX
193. Burkhardt, T., Özkurt, S., Schimpf, F., & Fichter, W. (2023, May). Development of a Datadriven Model for Prediction of Vibrational Discomfort in Helicopters. Proceedings of the 79th Annual Forum of the Vertical Flight Society.
BibTeX
BibTeX
191. Wettengl, N., Notter, S., & Fichter, W. (2022, January). Enhancing Updraft Observability by Optimal Path Planning.
AIAA SCITECH 2022 Forum.
https://doi.org/10.2514/6.2022-2216
BibTeX
BibTeX
189. Vigneron, A., Delchambre, S., Ziegler, T., & Fichter, W. (2022). Design of low-bandwidth attitude controllers for time-optimal transient behaviour.
BibTeX
188. Vigneron, A., Delchambre, S., Ziegler, T., & Fichter, W. (2022). Initialization of linear controllers for constrained time-optimal attitude control.
BibTeX
187. Steinleitner, A., Frenzel, V., Pfeifle, O., Denzel, J., & Fichter, W. (2022, January). Automatic Take-Off and Landing of Tailwheel Aircraft with Incremental Nonlinear Dynamic Inversion.
AIAA SCITECH 2022 Forum.
https://doi.org/10.2514/6.2022-1228
BibTeX
186. Schneider, M., & Fichter, W. (2022, January). Multi-Hypothesis Guidance With Interacting Multiple Model Filter.
AIAA SCITECH 2022 Forum.
https://doi.org/10.2514/6.2022-1846
BibTeX
185. Schimpf, F., Olucak, J., & Fichter, W. (2022, January). Robust Landing Site Detection for Flight over Small Solar System Bodies.
AIAA SCITECH 2022 Forum.
https://doi.org/10.2514/6.2022-0955
BibTeX
184. Schieni, R., Simsek, M., Cunis, T., Bilgen, O., & Burlion, L. (2022). Control of Bistable Structures Using a Modified Hybrid Position Feedback Controller.
AIAA SciTech Forum 2022.
https://doi.org/10.2514/6.2022-0922
Abstract
Bistable structures show promise for morphing applications as they have the capability of obtaining two stable shapes which do not require energy to be maintained. The vibration of a bistable structure has been modelled previously as a Duffing-Holmes oscillator. To control the motion of a bistable structure from one equilibrium point to the other, a hybrid unstable-then-stable position feedback controller has been successfully employed. The hybrid controller destabilizes the structure around the initial equilibrium position then stabilizes it around the second equilibrium point. Previously, the decision to switch from destabilization mode to stabilization mode is made based upon the position of the structure. In the present research, new methods for determining when to activate and deactivate the stabilizing and destabilizing control schemes are presented. The proposed methods employ optimization techniques, model predictive control, and energy methods to determine when to activate or deactivate each scheme. Results of numerical simulations for the proposed switching methods are presented in this work.BibTeX
183. Rothaupt, B., Grebing, B., & Fichter, W. (2022, May). Model-Based Optimization of a Tethering Device for Ultralight Helicopters.
Proceedings of the Vertical Flight Society 78th Annual Forum.
https://doi.org/10.4050/f-0078-2022-17514
BibTeX
182. Price, E., Liu, Y. T., Black, M. J., & Ahmad, A. (2022). Simulation and Control of Deformable Autonomous Airships in Turbulent Wind. In M. H. Ang Jr, H. Asama, W. Lin, & S. Foong (Eds.),
Intelligent Autonomous Systems 16 (pp. 608–626). Springer International Publishing.
https://doi.org/10.1007/978-3-030-95892-3_46
Abstract
Fixed wing and multirotor UAVs are common in the field of robotics. Solutions for simulation and control of these vehicles are ubiquitous. This is not the case for airships, a simulation of which needs to address unique properties, i) dynamic deformation in response to aerodynamic and control forces, ii) high susceptibility to wind and turbulence at low airspeed, iii) high variability in airship designs regarding placement, direction and vectoring of thrusters and control surfaces. We present a flexible framework for modeling, simulation and control of airships. It is based on Robot operating system (ROS), simulation environment (Gazebo) and commercial off the shelf (COTS) electronics, all of which are open source. Based on simulated wind and deformation, we predict substantial effects on controllability which are verified in real-world flight experiments. All our code is shared as open source, for the benefit of the community and to facilitate lighter-than-air vehicle (LTAV) research. (Source code: https://github.com/robot-perception-group/airship\_simulation.)BibTeX
181. Pfeifle, O., & Fichter, W. (2022, January). Time-Optimal Incremental Nonlinear Dynamic Inversion through Deadbeat Control.
AIAA SCITECH 2022 Forum.
https://doi.org/10.2514/6.2022-1596
BibTeX
180. Patel, M., Bandopadhyay, A., & Ahmad, A. (2022). Collaborative Mapping of Archaeological Sites Using Multiple UAVs. In M. H. Ang Jr, H. Asama, W. Lin, & S. Foong (Eds.),
Intelligent Autonomous Systems 16 (pp. 54–70). Springer International Publishing.
https://doi.org/10.1007/978-3-030-95892-3_5
Abstract
UAVs have found an important application in archaeological mapping. Majority of the existing methods employ an offline method to process the data collected from an archaeological site. They are time-consuming and computationally expensive. In this paper, we present a multi-UAV approach for faster mapping of archaeological sites. Employing a team of UAVs not only reduces the mapping time by distribution of coverage area, but also improves the map accuracy by exchange of information. Through extensive experiments in a realistic simulation (AirSim), we demonstrate the advantages of using a collaborative mapping approach. We then create the first 3D map of the Sadra Fort, a 15th Century Fort located in Gujarat, India using our proposed method. Additionally, we present two novel archaeological datasets recorded in both simulation and real-world to facilitate research on collaborative archaeological mapping. For the benefit of the community, we make the AirSim simulation environment, as well as the datasets publicly available (Project web page: http://patelmanthan.in/castle-ruins-airsim/).BibTeX
179. Olucak, J., Schimpf, F., Pinchetti, F., & Fichter, W. (2022, January). Energy Aware Trajectory Generation for a Novel Cometary Lander Concept.
AIAA SCITECH 2022 Forum.
https://doi.org/10.2514/6.2022-0954
BibTeX
Abstract
Autonomous soaring constitutes an appealing academic sample problem for investigating machine learning methods within the scope of aerospace guidance, navigation, and control. The stochastic nature of small-scale meteorological phenomena renders the task of localizing and exploiting thermal updrafts suited for applying a reinforcement learning approach. Within this work, we present a training setup for learning an integrated control strategy for autonomous localization and exploitation of thermal updrafts. In particular, we propose a deep artificial neural network featuring a Long Short-Term Memory to represent the policy. Instead of just implementing a static control law, the recurrent structure facilitates observability and enables mapping the hard-to-model dynamics of thermal updrafts. The end-to-end type control policy integrates an estimator for updraft localization, including a latent state-transition model. We show in simulation, that the trained agent autonomously localizes and exploits stochastic, non-stationary thermal updrafts. The unaltered reinforcement learning setup can be deployed to further improve the control policy through real-world interactions.BibTeX
177. Hein, F., Wiedenroth, R., Notter, S., & Fichter, W. (2022, January). Flight Mechanical Analysis and Nonlinear Controller Design for a 4-Line Kite.
AIAA SCITECH 2022 Forum.
https://doi.org/10.2514/6.2022-1229
BibTeX
176. Cunis, T., Kolmanovsky, I., & Cesnik, C. E. S. (2022). Control Co-Design Optimization: Integrating nonlinear controllability into a multidisciplinary design process.
AIAA SciTech Forum 2022.
https://doi.org/10.2514/6.2022-2176
Abstract
This paper presents a new control co-design optimization (CCDO) framework to integrate controller-agnostic, nonlinear viability constraints informed by the solutions to optimal control problems into the multidisciplinary design process. To implement the optimization, procedures to evaluate the sensitivity of the controllability constraint to variations in the design are defined. Two supersonic aircraft examples associated with low-speed flight regime constraints illustrate the new methodology and the steps involved in the process.BibTeX
BibTeX
174. Bertolin, R. M., Barbosa, G. C., Cunis, T., Kolmanovsky, I., & Cesnik, C. E. S. (2022). Gust Rejection of a Supersonic Aircraft During Final Approach.
AIAA SciTech Forum 2022.
https://doi.org/10.2514/6.2022-2174
Abstract
This paper presents a methodology based on optimal control to characterize the ability of a supersonic aircraft to reject atmospheric disturbances during its final approach to land. A longitudinal flight dynamics model is considered for which a set of rejectable disturbances is defined based on the values of three proposed barrier functionals. The problem of finding an admissible control input is then converted into a discrete nonlinear optimal control problem (NOCP) by defining an objective function based on an augmented discretized nonlinear dynamics that takes into account the disturbance models. It uses the Kreisselheimer-Steinhauser aggregation function to enable the application of gradient-based optimization methods. As an illustration, such an approach is applied to three different configurations of a supersonic business jet in the landing flight phase and under gust and turbulence disturbances.BibTeX
173. Welsch, M., & Fichter, W. (2021, January). Ground-Based Turn Coordination for VTOL Vehicles with Wind Compensation.
AIAA Scitech 2021 Forum.
https://doi.org/10.2514/6.2021-0255
Abstract
Especially in urban environments where space is closely confined, VTOL vehicles used for Urban Air Mobility will need to be controlled with respect to ground in the horizontal plane in order to comply with path restrictions set by fixed obstacles. This work presents a control scheme in the horizontal plane that allows a pilot to command ground-based velocities with respect to the vehicle heading and inherently coordinates the turn whenever a change of heading is commanded. The turn coordination algorithm is adapted based on the flight state of the vehicle in order to compensate for the varying influence of wind. It is shown that the adaption improves the control performance during turning flight.BibTeX
172. Vigneron, A., Delchambre, S., Ziegler, T., & Fichter, W. (2021, January). A Transient-Suppressing Initialization for Low-Bandwidth Attitude Controllers.
Proceedings of the AIAA Scitech 2021 Forum.
https://doi.org/10.2514/6.2021-1563
BibTeX
171. Skibik, T., Liao-McPherson, D., Cunis, T., Kolmanovsky, I., & Nicotra, M. M. (2021). Feasibility Governor for Linear Model Predictive Control.
Proceedings of the American Control Conference, 2329–2335.
https://doi.org/10.23919/ACC50511.2021.9483054
Abstract
This paper introduces the Feasibility Governor (FG): an add-on unit that enlarges the region of attraction of Model Predictive Control by manipulating the reference to ensure that the underlying optimal control problem remains feasible. The FG is developed for linear systems subject to polyhedral state and input constraints. Offline computations using polyhedral projection algorithms are used to construct the feasibility set. Online implementation relies on the solution of a convex quadratic program that guarantees recursive feasibility. The closed-loop system is shown to satisfy constraints, achieve asymptotic stability, and exhibit zero-offset tracking.BibTeX
170. Schlichting, M. R., Notter, S., & Fichter, W. (2021, January). LSTM-Based Spatial Encoding: Explainable Path Planning for Time-Variant Multi-Agent Systems.
Proceedings of the AIAA Scitech 2021 Forum.
https://doi.org/10.2514/6.2021-1860
BibTeX
169. Schimpf, F., Notter, S., Groß, P., & Fichter, W. (2021, January). Multi-Agent Reinforcement Learning for Thermalling in Updrafts.
AIAA Scitech 2021 Forum.
https://doi.org/10.2514/6.2021-0864
BibTeX
168. Rothaupt, B., Notter, S., & Fichter, W. (2021, January). Autonomous Soaring Policy Initialization Through Value Iteration.
AIAA Scitech 2021 Forum.
https://doi.org/10.2514/6.2021-2012
BibTeX
167. Price, E., Liu, Y. T., Black, M. J., & Ahmad, A. (2021, June). Simulation and Control of Deformable Autonomous Airships in Turbulent Wind. 16th International Conference on Intelligent Autonomous System (IAS).
BibTeX
166. Pfeifle, O., Frangenberg, M., Notter, S., Denzel, J., Bergmann, D., Schneider, J., Scholz, W., Fichter, W., & Strohmayer, A. (2021). Distributed Electric Propulsion for Yaw Control: Testbeds, Control Approach, and Flight Testing.
AIAA Aviation 2021 Forum.
https://doi.org/10.2514/6.2021-3192
BibTeX
165. Pfeifle, O., & Fichter, W. (2021). Energy Optimal Control Allocation for INDI Controlled Transition Aircraft.
AIAA Scitech 2021 Forum.
https://doi.org/10.2514/6.2021-1457
BibTeX
164. Notter, S., Schimpf, F., & Fichter, W. (2021, January). Hierarchical Reinforcement Learning Approach Towards Autonomous Cross-Country Soaring.
AIAA Scitech 2021 Forum.
https://doi.org/10.2514/6.2021-2010
BibTeX
163. Lai, B., Cunis, T., & Burlion, L. (2021). Nonlinear Trajectory Based Region of Attraction Estimation for Aircraft Dynamics Analysis.
AIAA Scitech 2021 Forum.
https://doi.org/10.2514/6.2021-0253
Abstract
© 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All Rights Reserved. Current flight control validation is heavily based on linear analysis and high fidelity, nonlinear simulations. Continuing developments of nonlinear analysis tools for flight control has greatly enhanced the validation process. Many analysis tools are reliant on assuming the analytical flight dynamics but this paper proposes an approach using only simulation data. First, this paper presents improvements to a method for estimating the region of attraction (ROA) of nonlinear systems governed by ordinary differential equations (ODEs) based only on trajectory measurements. Faster and more accurate convergence to the true ROA results. These improvements make the proposed algorithm feasible in higher-dimensional and more complex systems. Next, these tools are used to analyze the four-state longitudinal dynamics of NASA's Generic Transport Model (GTM) aircraft. A piecewise polynomial model of the GTM is used to simulate trajectories and the developed analysis tools are used to estimate the ROA around a trim condition based only on this trajectory data. Finally, the algorithm presented is extended to estimate the ROA of finitely many equilibrium point systems and of general equilibrium set (arbitrary equilibrium points and limit cycles) systems.BibTeX
BibTeX
161. Özkurt, S., Rath, T., Fichter, W., Dieterich, O., Priems, M., Nooij, S. A. E., & Bülthoff, H. H. (2020, October). From Helicopter Vibrations to Passenger Perceptions: A Closer Look on Standards.
Proceedings of the 76th Annual Forum.
https://doi.org/10.4050/F-0076-2020-16433
BibTeX
160. Özkurt, S., Rath, T., Fichter, W., Dieterich, O., Priems, M., Nooij, S. A. E., & Bülthoff, H. H. (2020, October). From Helicopter Vibrations to Passenger Perceptions: A Closer Look on Standards. Proceedings of the 76th Annual Forum.
BibTeX
Abstract
Rate-limited actuators introduce nonlinearities into a control system, which results in a loss of phase and a reduction of amplitude of the control signal. These effects have been identified as being a main contributor to pilot induced oscillation incidents and therefore methods were developed in the field of aircraft control systems in order to compensate the detrimental effects. This work evaluates the application of such a method when used for rate-limited electric motors in a large-scale (man-carrying) multicopter vehicle. An approach using a feedback-type method is presented and its performance evaluated using a simulation model. It can be shown that the approach improves the vehicle behavior and stability in situations where extreme changes of the motor turning speeds are required.BibTeX
158. Stephan, J., Notter, S., Pfeifle, O., Pinchetti, F., & Fichter, W. (2020). Spline Trajectory Planning and Guidance for Fixed-Wing Drones.
Proceedings of the AIAA Scitech 2020 Forum.
https://doi.org/10.2514/6.2020-0372
BibTeX
157. Stephan, J., & Fichter, W. (2020, January). Active Battery Charge Drift Stabilization for Redundant Multirotors.
Proceedings of the AIAA Scitech 2020 Forum.
https://doi.org/10.2514/6.2020-1833
BibTeX
156. Friedrich, M., & Fichter, W. (2020, January). Multibody model of a large multicopter with arbitrary propeller axes of rotation.
Proceedings of the AIAA Scitech 2020 Forum.
https://doi.org/10.2514/6.2020-1505
BibTeX
155. Cunis, T., Liao-McPherson, D., Kolmanovsky, I., & Burlion, L. (2020). Model-Predictive Spiral and Spin Upset Recovery Control for the Generic Transport Model Simulation.
2020 IEEE Conference on Control Technology and Applications, 1–7.
https://doi.org/10.1109/CCTA41146.2020.9206158
Abstract
© 2020 IEEE. Aircraft upsets are a major cause of fatalities in civil aviation. Unfortunately, recovery from upset scenarios is challenging due to the combination of nonlinearities, actuator limits, and upset modes. In this paper, we consider the use of Model-Predictive Control (MPC) in combination with a recently proposed piecewise polynomial prediction model, for six degree-of-freedom upset recovery. MPC naturally handles nonlinearities and constraints and has a provably large closed-loop region of attraction making it an appealing methodology for upset recovery problems. We present a recovery formulation then illustrate its utility through high fidelity simulation case studies, using the Generic Transport Model, of recovery from oscillatory spin and steep spiral upset conditions.BibTeX
154. Tallamraju, R., Salunkhe, D., Rajappa, S., Ahmad, A., Karlapalem, K., & Shah, S. V. (2019). Motion Planning for Multi-Mobile-Manipulator Payload Transport Systems.
15th IEEE International Conference on Automation Science and Engineering, 1469–1474.
https://doi.org/10.1109/COASE.2019.8842840
BibTeX
153. Pfeifle, O., Fichter, W., Bergmann, D., Denzel, J., Strohmayer, A., Schollenberger, M., & Lutz, T. (2019, June). Precision performance measurements of fixed-wing aircraft with wing tip propellers.
Proceedings of the AIAA Aviation 2019 Forum.
https://doi.org/10.2514/6.2019-3088
BibTeX
152. Notter, S., Zürn, M., Groß, P., & Fichter, W. (2019, January). Reinforced Learning to Cross-Country Soar in the Vertical Plane of Motion.
Proceedings of the AIAA Scitech 2019 Forum.
https://doi.org/10.2514/6.2019-1420
BibTeX
151. Karásek, M., Percin, M., Cunis, T., van Oudheusden, B. W., De Wagter, C., Remes, B. D. W., & de Croon, G. C. H. E. (2019). Accurate position control of a flapping-wing robot enabling free-flight flow visualisation in a wind tunnel.
International Journal of Micro Air Vehicles,
11.
https://doi.org/10.1177/1756829319833683
Abstract
© The Author(s) 2019. Flow visualisations are essential to better understand the unsteady aerodynamics of flapping wing flight. The issues inherent to animal experiments, such as poor controllability and unnatural flapping when tethered, can be avoided by using robotic flyers that promise for a more systematic and repeatable methodology. Here, we present a new flapping-wing micro air vehicle (FWMAV)-specific control approach that, by employing an external motion tracking system, achieved autonomous wind tunnel flight with a maximum root-mean-square position error of 28 mm at low speeds (0.8–1.2 m/s) and 75 mm at high speeds (2–2.4 m/s). This allowed the first free-flight flow visualisation experiments to be conducted with an FWMAV. Time-resolved stereoscopic particle image velocimetry was used to reconstruct the three-dimensional flow patterns of the FWMAV wake. A good qualitative match was found in comparison to a tethered configuration at similar conditions, suggesting that the obtained free-flight measurements are reliable and meaningful.BibTeX
150. Groß, P., Notter, S., & Fichter, W. (2019, January). Estimating Total Energy Compensated Climb Rates from Position Trajectories.
AIAA Scitech 2019 Forum.
https://doi.org/10.2514/6.2019-0828
BibTeX
149. Geshnizjani, R., Kornienko, A., Ziegler, T., Loehr, J., & Fichter, W. (2019, January). Optimal Initial Gimbal Angles for Agile Slew Maneuvers with Control Moment Gyroscopes.
Proceedings of the AIAA Scitech 2019 Forum.
https://doi.org/10.2514/6.2019-0936
BibTeX
148. Cunis, T., Liao-McPherson, D., Condomines, J. P., Burlion, L., & Kolmanovsky, I. (2019). Economic Model-Predictive Control Strategies for Aircraft Deep-stall Recovery with Stability Guarantees.
Proceedings of the IEEE Conference on Decision and Control, 157–162.
https://doi.org/10.1109/CDC40024.2019.9030207
Abstract
Aircraft upset recovery requires aggressive control actions to handle highly nonlinear aircraft dynamics and critical state and input constraints. Model predictive control is a promising approach for returning the aircraft to the nominal flight envelope, even in the presence of altered dynamics or actuator limits; however, proving stability of such strategies requires careful algebraic or semi-algebraic analysis of both the system and the proposed control scheme, which can be challenging for realistic control systems. This paper develops economic model predictive strategies for recovery of a fixed-wing aircraft from deep-stall. We provide rigorous stability proofs using sum-of-squares programming and compare several economic, nonlinear, and linear model predictive controllers.BibTeX
147. Ahmad, A., Price, E., Tallamraju, R., Saini, N., Lawless, G., Ludwig, R., Martinovic, I., Bülthoff, H. H., & Black, M. J. (2019, November). AirCap -- Aerial Outdoor Motion Capture. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), Workshop on Aerial Swarms.
BibTeX
146. Stephan, J., & Fichter, W. (2018, January). Gain-Scheduled Multivariable Flight Control under Uncertain Trim Conditions.
Proceedings of the 2018 AIAA Guidance, Navigation, and Control Conference.
https://doi.org/10.2514/6.2018-1130
BibTeX
145. Notter, S., Schrapel, P., Groß, P., & Fichter, W. (2018, January). Estimation of Multiple Thermal Updrafts Using a Particle Filter Approach.
2018 AIAA Guidance, Navigation, and Control Conference.
https://doi.org/10.2514/6.2018-1854
BibTeX
144. Notter, S., Schrapel, P., Groß, P., & Fichter, W. (2018, January). Estimation of Multiple Thermal Updrafts Using a Particle Filter Approach.
Proceedings of the 2018 AIAA Guidance, Navigation, and Control Conference.
https://doi.org/10.2514/6.2018-1854
BibTeX
143. Gerboni, C. A., Geluardi, S., Fichter, W., & Bülthoff, H. H. (2018, May). Model-Following Control and Actuator Limits Analysis to Transform Helicopters into Personal Aerial Vehicles. Proceedings of the AHS International 74th Annual Forum & Technology Display.
BibTeX
142. Geiss, I., Notter, S., Strohmayer, A., & Fichter, W. (2018, June). Optimized Operation Strategies for Serial Hybrid-Electric Aircraft.
Proceedings of the 2018 Aviation Technology, Integration, and Operations Conference.
https://doi.org/10.2514/6.2018-4230
BibTeX
141. Friedrich, M., & Fichter, W. (2018, January). Optimization of the mass ratio for a general multi-rotor aircraft.
Proceedings of the 2018 AIAA Atmospheric Flight Mechanics Conference.
https://doi.org/10.2514/6.2018-0531
BibTeX
140. Cunis, T., Leth, T., Totu, L. C., & la Cour-Harbo, A. (2018). Identification of Thrust, Lift, and Drag for Deep-stall Flight Data of a Fixed-wing Unmanned Aircraft.
2018 International Conference on Unmanned Aircraft Systems, 531–538.
https://doi.org/10.1109/ICUAS.2018.8453340
Abstract
© 2018 IEEE. In this paper, we consider a small unmanned aircraft and data collected during regular and deep-stall flight. We present an identification method for the thrust force generated by the propulsion system based on the in-flight measurements where we make use of the well-known linear and quadratic approximations of the lift and drag coefficients, respectively, for low angles of attack. This overcomes the lack of propeller thrust measurements and the obtained models are successfully evaluated against CFD simulation. The identified thrust model proves applicable beyond low angles of attack, thus enabling force estimation in the full flight envelope.BibTeX
139. Cunis, T., Burlion, L., & Condomines, J.-P. (2018). Piece-wise identification and analysis of the aerodynamic coefficients, trim conditions, and safe sets of the generic transport model.
AIAA Guidance, Navigation, and Control Conference.
https://doi.org/10.2514/6.2018-1114
Abstract
© 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. Aeronautical research has investigated the Generic Transport Model (GTM) in windtunnel studies and provides today an elaborated aerodynamic model for designing methods dedicated to convergence analysis or control problems of aerial vehicles. In this paper, we propose a novel approach for fitting aerodynamic coefficients, namely piece-wise polynomial identification, which is based on measurements in both pre- and post-stall region. The developed method suggests a systematic approach to determine full envelope better than the purely polynomial models published yet. As a result, an analysis of GTM's longitudinal trim conditions has been successfully applied on the piece-wise identified model and achieves better results than polynomial models. Based on the trim conditions, safe set computation for linear-quadratic controllers is argued to be a powerful tool for verification of nonlinear control systems. Using common and multiple Lyapunov-functions theory, we are able to present a method for the safe set computation with piece-wise defined systems dynamics.BibTeX
138. Cunis, T., & Baskaya, E. (2018). Performance of Unmanned Aircrafts in the Event of Loss-of-control. 10th International Micro Air Vehicle Conference and Competition.
BibTeX
137. Kornienko, A., Dhole, P., Geshnizjani, R., Jamparueang, P., & Fichter, W. (2017, May). Determing Spacecraft Moment of Inertia using In-Orbit Data. Proceedings of the 10th International ESA Conference on Guidance, Navigation & Control Systems.
BibTeX
136. Gerboni, C. A., Geluardi, S., Venrooij, J., Joos, A., Fichter, W., & Buelthoff, H. H. (2017, January). Development of model-following control laws for helicopters to achieve personal aerial vehicle handling qualities.
Proceedings of the 2017 AIAA Modeling and Simulation Technologies Conference.
https://doi.org/10.2514/6.2017-1312
BibTeX
135. Gerboni, C., Geluardi, S., Fichter, W., & Bülthoff, H. (2017, May). Investigation and Evaluation of Control Design Requirements for future Personal Aerial Vehicles. Proceedings of the AHS International 73rd Annual Forum & Technology Display.
BibTeX
134. Cunis, T., Condomines, J.-P., & Burlion, L. (2017). Full-envelope, six-degrees-of-freedom trim analysis of unmanned aerial systems based on piece-wise polynomial aerodynamic coefficients.
2017 Workshop on Research, Education and Development of Unmanned Aerial Systems, 108–113.
https://doi.org/10.1109/RED-UAS.2017.8101652
Abstract
© 2017 IEEE. Polynomial models for the aerodynamic coefficients are not able to incorporate the full-envelope aerodynamics and offer only vaguely fitting at high angles of attack. In this paper, we propose a novel approach, namely piece-wise polynomial identification; this method provides a systematic approach for full-envelope aerodynamic fitting, considering measurements both of the pre-stall and post-stall region. As a result, a six-degrees-of-freedom, full-envelope analysis of trim conditions has successfully been applied for a large unmanned aerial vehicle.BibTeX
133. Cunis, T., Burlion, L., & Condomines, J.-P. (2017). Non-linear Analysis and Control Proposal for In-flight Loss-of-control. Preprints of the 20th IFAC World Congress, 10681–10685.
Abstract
In-flight loss-of-control (LOC-I) still poses a severe threat to today's commercial aviation. Hence, we review the literature for non-linear analysis and control methods of LOC-I and upset recovery. Using state-of-the-art methods such as continuation theory and reachability estimation, we sketch an analysis of an aircraft's flight envelope in terms of its trim conditions and propose control approaches both within and outside the envelope.BibTeX
132. Zürn, M., Morton, K., Heckmann, A., McFadyen, A., Notter, S., & Gonzalez, F. (2016). MPC controlled multirotor with suspended slung Load: System architecture and visual load detection.
Proceedings of the 2016 IEEE Aerospace Conference, 1–11.
https://doi.org/10.1109/AERO.2016.7500543
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131. Stephan, J., & Fichter, W. (2016, January). Fast Generation of Landing Paths for Fixed-Wing Aircraft with Thrust Failure.
Proceedings of the 2016 AIAA Guidance, Navigation, and Control Conference.
https://doi.org/10.2514/6.2016-1874
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130. Schmitt, L., & Fichter, W. (2016). Smooth Singularity Free Solution to the Three-Dimensional Bearings-Only Tracking Problem.
Proceedings of the 2016 AIAA Guidance, Navigation, and Control Conference, 1858.
https://doi.org/10.2514/6.2016-1858
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129. Rath, T., Richter, T., Steinwandel, A., & Fichter, W. (2016, May). Emulation of Whirl Flutter on a Stable Helicopter Using Trailing Edge Flaps. AHS - Forum 72 Proceedings.
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128. Notter, S., Heckmann, A., Mcfadyen, A., & Gonzalez, F. (2016). Modelling, Simulation and Flight Test of a Model Predictive Controlled Multirotor with Heavy Slung Load.
IFAC-PapersOnLine, 20th IFAC Symposium on Automatic Control in AerospaceACA 2016,
49, Article 17.
https://doi.org/10.1016/j.ifacol.2016.09.032
BibTeX
127. Kornienko, A., Rieber, J., Ott, T., Geshnizjani, R., Fichter, W., Forshaw, J., & Aglietti, G. (2016, August). Experimental Verification of Attitude Control System for Agile Spacecraft. 20th IFAC Symposion on Automatic Control in Aerospace.
Abstract
This paper addresses the design and verification of an attitude control system for an agile satellite using experimental data. Typical agile satellites are equipped with control momentum gyros, which allow for the generation of high internal reaction torques and hence attitude maneuvers with high angular rates. The architecture of the attitude control system with design implications is presented and discussed. In order to mitigate the risks associated with design and verification of the highly demanding agile attitude control, experimental results involving a hardware in-the-loop demonstrator are presented. The overall design process and closed loop performance evaluation allows an increasing technology readiness level for target missions.BibTeX
126. King, F., Steinwandel, A., & Fichter, W. (2016). Application Issues for In-Flight Tracking Control Using Trailing Edge Flaps. Proceedings of the AHS International 72nd Annual Forum & Technology Display.
BibTeX
125. Gros, M., & Fichter, W. (2016, January). G3-Continuous Trajectory Design For Fixed-Wing Aircraft Based On 6-DoF Kinematics.
Proceedings of the 2016 AIAA Guidance, Navigation, and Control Conference.
https://doi.org/10.2514/6.2016-1873
BibTeX
124. Geshnizjani, R., Kornienko, A., & Fichter, W. (2016, August). Angular Momentum Based Steering Approach for Control Moment Gyroscopes.
Proceedings of the 20th IFAC Symposium on Automatic Control in Aerospace 2016.
https://doi.org/10.1016/j.ifacol.2016.09.025
BibTeX
123. Gerboni, C. A., Joos, A., Nieuwenhuizen, F. M., Fichter, W., & Buelthoff, H. (2016, January). Control Augmentation Strategies for Helicopters used as Personal Aerial Vehicles.
Proceedings of the 2016 AIAA Modeling and Simulation Technologies Conference.
https://doi.org/10.2514/6.2016-2137
BibTeX
122. Cunis, T., Karásek, M., & de Croon, G. C. H. E. (2016). Precision Position Control of the DelFly II Flapping-wing Micro Air Vehicle in a Wind-tunnel. 8th International Micro Air Vehicle Conference and Competition.
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120. Steinwandel, A., & Fichter, W. (2015, May). Effects of 2/rev Trailing Edge Flap Input on Helicopter Vibrations for Concurrent Vibration and Noise Reduction. Proceedings of the AHS International 71st Annual Forum & Technology Display.
BibTeX
119. Sanz, D., Ahmad, A., & Lima, P. (2015). Onboard robust person detection and tracking for domestic service robots.
Robot 2015: Second Iberian Robotics Conference, 547–559.
https://doi.org/10.1007/978-3-319-27149-1_42
BibTeX
BibTeX
117. Kueke, R., Mueller, P., Polenz, S., Reichel, R., Pinchetti, F., Stephan, J., Joos, A., & Fichter, W. (2015, October). Fly-by-Wire for CS23 Aircraft - Core Technology for General Aviation and RPAS. Proceedings of the Seventh European Aeronautics Days.
BibTeX
116. Grzymisch, J., Fichter, W., Losa, W. D., & Casasco, M. (2015). Bearings-Only Rendezvous with Enhanced Performance. Selected Papers of the Third CEAS Specialist Conference on Guidance, Navigation and Control, 571–590.
BibTeX
115. Frangenberg, M., Stephan, J., & Fichter, W. (2015, January). Fast Actuator Fault Detection and Reconfiguration for Multicopters. Proceedings of the 2015 AIAA Guidance, Navigation, and Control Conference.
BibTeX
114. Bamber, D., Forshaw, J., Frame, T., Aglietti, G., Geshnizjani, R., Goerries, S., Kornienko, A., Levenhagen, J., Gao, Y., & Chanik, A. (2015, October). Absolute Attitude Determination System for a Spherical Air Bearing Testbed. 66th International Astronautical Congress.
Abstract
Three degree of freedom (3-DOF) ACS satellite testbed systems are essential hardware-in-loop testing facilities for the construction of a wide range of intelligent AOCS algorithms. Intrepid is a 3-DOF spherical air-bearing satellite testbed custom designed at the Surrey Space Centre, UK, and installed on-site at Airbus DS in Friedrichshafen, Germany for the AOCS & GNC Group. The testbed consists of a table-top for the mounting of satellite hardware, 4 control moment gyroscopes (CMGs) mounted in a pyramid configuration and a sensor suite including an IMU. Under normal operation the CMGs can be used to command the table to required angles thus testing the AOCS alogrithms using only the IMU as an attitude sensor. Satellites require long-term stable and short-term high resolution attitude measurements, which are fused on-board to estimate the attitude. The IMU provides high resolution attitude information, but has the drawback of not knowing the initial attitude and also drifting over time. This paper concerns the development of an absolute attitude determination system (AADS) that utilises an infra-red camera, a series of LEDs positioned across the table-top, and intelligent software to independently determine the absolute attitude of the table-top. The system thus provides long-term stable attitude measurements and overcomes the shortcomings of the IMU. The newly installed AADS software contains vision processing and triangulation algorithms that provide real-time absolute attitude information to the host computer. The vanilla system can achieve attitude determination accuracy within 1 degree in yaw and 2 degrees in pitch and roll. The software can calibrate itself compensating for intrinsic and extrinsic offsets including incorrectly placed LEDs and a misaligned camera system. A sub-pixel feature detection technique is utilised to enhance the accuracy of the system. It is shown that by modifying the position of the LEDs or modifying the placement of the camera, more optimal attitude accuracies along different axes can be obtained.This paper will detail the main operation of the system from both a hardware and software perspective and provide experimental results during operation.BibTeX
113. Ahmad, A., & Lima, P. (2015). Dataset Suite for Benchmarking Perception in Robotics. International Conference on Intelligent Robots and Systems (IROS) 2015.
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112. King, F. A., Steinwandel, A., & Fichter, W. (2014, May). Performance Characteristics of Symmetrized In-Flight Tracking Control. Proceedings of the AHS 70th Annual Forum.
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111. Weimer, F., Frangenberg, M., & Fichter, W. (2013, August). Pipelined Particle Filter with Non-Observability Measure for On-Board Navigation with MAVs.
Proceedings of 2013 AIAA Guidance, Navigation, and Control (GNC) Conference.
https://doi.org/10.2514/6.2013-5247
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110. Vogel, H., Fichter, W., Choe, R., Xargay, E., & Hovakimyan, N. (2013, August). Magnetic Momentum Control of a Satellite Augmented with an L1 Adaptive Controller.
Proceedings of the AIAA Guidance, Navigation, and Control (GNC) Conference 2013.
https://doi.org/10.2514/6.2013-5092
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109. Troppan, A., Guerreiro, E., Celiberti, F., Santos, G., Ahmad, A., & Lima, P. (2013).
Unknown-color spherical object detection and tracking. 1–4.
https://doi.org/10.1109/Robotica.2013.6623533
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108. Trittler, M., Rothermel, T., & Fichter, W. (2013). Visual Servoing Based Landing Approach Controller for Fixed-Wing MAVs. Proceedings of the 19th IFAC Symposium on Automatic Control in Aerospace 2013, 19, September.
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107. Trittler, M., Fichter, W., & Schöttl, A. (2013, September). Return Strategies for Fixed-Wing MAVs after Loss of GPS. IFAC Symposium on Automatic Control in Aerospace.
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106. Souanef, T., & Fichter, W. (2013). Adaptive Altitude Hold of a Small Fixed Wing UAV. Proceedings of the 19th IFAC Symposium on Automatic Control in Aerospace 2013, 19.
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105. Souanef, T., Pinchetti, F., & Fichter, W. (2013). L1 Adaptive Control for Systems with Matched Stochastic Disturbance. Proceedings of the EuroGNC 2013, 2nd CEAS Specialist Conference on Guidance, Navigation & Control, Delft University of Technology, 297–313.
BibTeX
104. Grzymisch, J., Fichter, W., Casasco, M., & Losa, D. (2013). A Spherical Coordinate Parameterization for an In-Orbit Bearings-Only Navigation Filter. Proceedings of the Advances in Aerospace Guidance, Navigation and Control Conference, 215–231.
BibTeX
103. Grzymisch, J., Fehse, W., Fichter, W., Casasco, M., & Losa, D. (2013). On the Issues and Requirements of Bearings-Only Guidance and Navigation for In-Orbit Rendezvous.
Proceedings of the 64 International Astronautical Congress,
64.
https://doi.org/10.1007/978-3-319-17518-8_33
BibTeX
102. Gros, M., Schoettl, A., & Fichter, W. (2013, August). Spline and OBB-based Path-Planning for Small UAVs with the Finite Receding-Horizon Incremental-Sampling Tree Algorithm.
Proceedings of the AIAA Guidance, Navigation, and Control (GNC) Conference 2013.
https://doi.org/10.2514/6.2013-4788
BibTeX
101. Casasco, M., Criado, G. S., Weikert, S., Eggert, J., Hirth, M., Ott, T., & Su, H. (2013, August). Pointing Error Budgeting for High Pointing Accuracy Mission using the Pointing Error Engineering Tool.
Proceedings of the AIAA Guidance, Navigation, and Control (GNC) Conference 2013.
https://doi.org/10.2514/6.2013-5251
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97. Weimer, F., Rothermel, T., & Fichter, W. (2012, February). Adaptive actuator fault detection and identification for UAV applications.
Proceedings of the 1st IFAC Workshop on Embedded Guidance, Navigation and Control in Aerospace.
https://doi.org/10.3182/20120213-3-IN-4034.00015
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96. Weikert, S., Wiegand, A., Fichter, W., & Saage, R. (2012). Coupled Mission and GNC Analysis for Space Robotic Missions”. International Astronautical Congress, 63.
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95. King, F. A., Maurice, J.-B., Fichter, W., Dieterich, O., & Konstanzer, P. (2012). In-Flight Tracking Control for Helicopters using Active Trailing Edge Flaps. Proceedings of the AIAA Guidance, Navigation, and Control Conference 2012.
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94. Joos, A., Heritier, P., Huber, C., & Fichter, W. (2012, February). Method for parallel FPGA implementation of nonlinear model predictive control. Proceedings of the 1st IFAC Workshop on Embedded Guidance, Navigation and Control in Aerospace.
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93. Gros, M., Grimm, W., Schöttl, A., & Fichter, W. (2012). Finite receding-horizon incremental-sampling tree with application to a fixed-wing UAV. Proceedings of the 1st IFAC Workshop on Embedded Guidance, Navigation and Control in Aerospace, 1, Article 1.
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92. Winkler, S., Cirillo, F., Ergenzinger, K., Ott, T., Wilhelm, R., & Zaunick, E. (2011, June). High-Precision Attitude Determination and Control of the EUCLID Spacecraft: Challenges and Solutions. Proceedings of the 8th International ESA Conference on Guidance, Navigation & Control Systems.
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91. Trittler, M., Su, H., Fichter, W., & Schoettl, A. (2011, June). Intelligent Camera as Subsystem for Vision-Aided On-Board Navigation of MAVs. Proc. ESA GNC Conference.
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90. Ott, T., Fichter, W., Bennani, S., & Winkler, S. (2011, June). Coherent Precision Pointing Control Design based on Hinf-Closed Loop Shaping. Proceedings of the 8th International ESA Conference on Guidance, Navigation & Control Systems.
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89. Ott, T., Benoit, A., Van den Braembussche, P., & Fichter, W. (2011, June). ESA Pointing Error Engineering Handbook. Proceedings of the 8th International ESA Conference on Guidance, Navigation & Control Systems.
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88. M., G., M., N., A., S., & Fichter, W. (2011). Motion Planning for a Fixed-Wing MAV Incorporating Closed-Loop Dynamics Motion Primitives and Safety Maneuvers.
Selected Papers of the 1st CEAS Specialist Conference on Guidance, Navigation and Control, 247–260.
https://doi.org/10.1007/978-3-642-19817-5_20
BibTeX
87. Lima, P., Santos, P., Oliveira, R., Ahmad, A., & Santos, J. (2011). Cooperative Localization Based on Visually Shared Objects.
RoboCup 2010: Robot Soccer World Cup XIV, 350–361.
https://doi.org/10.1007/978-3-642-20217-9_30
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86. Joos, A., Weimer, F., & Fichter, W. (2011, June). Path Planning with FPGAs for UAV Applications. Proceedings of the 8th International ESA Conference on Guidance, Navigation & Control Systems.
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85. Joos, A., Müller, M. A., Baumgärtner, D., Fichter, W., & Allgöwer, F. (2011). Nonlinear Predictive Control Based on Time-Domain Simulation for Automatic Landing. Proceedings of the AIAA Guidance, Navigation, and Control Conference 2011, 2.
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84. Joos, A., & Fichter, W. (2011). Parallel Implementation of Constrained Nonlinear Model Predictive Controller for an FPGA-based Onboard Flight Computer,.
Selected Papers of the 1st CEAS Specialist Conference on Guidance, Navigation and Control.
https://doi.org/10.1007/978-3-642-19817-5_22
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83. Saage, R., Schleicher, A., & Fichter, W. (2010, August). Method for LFT Calculation with High Order Parametric Systems.
Proceedings of the AIAA Guidance Navigation and Control Conference 2010.
https://doi.org/10.2514/6.2010-8200
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82. Saage, R., Ross, R., Schleicher, A., & Fichter, W. (2010, August). Controller Design Method for Drag-Free Systems with Micro-Propulsion Constraints.
Procedings of the AIAA Guidance Navigation and Control Conference 2010.
https://doi.org/10.2514/6.2010-8200
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81. Kopfstedt, T., Restle, M.-O., & Grimm, W. (2010, September). Terrain Optimized Nonholonomic Following of Vehicle Tracks. Proceedings of the 7th IFAC Symposium on Intelligent Autonomous Vehicles 2010.
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80. Joos, A., Häfner, A., Weimer, F., & Fichter, W. (2010, August). Quadrocopter Ground Effect Compensation with Sliding Mode Control. Proceedings of the AIAA Guidance Navigation and Control Conference 2010.
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79. Joos, A., & Fichter, W. (2010, August). Yaw Guidance for Airships under low Airspeed Conditions. AIAA Guidance Navigation and Control Conference 2010.
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78. Grynagier, A., Vitale, S., & Fichter, W. (2010, June). The Data Analysis for the LISA Pathfinder Drift Mode. Journal of Physics Conference Series, 8th International LISA Symposium.
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77. Fach, M., Well, K. H., Salomon, U., & Weimer, F. (2010, August). Camera-Aided Navigation Sensor for Unmanned Blimp with low Trajectory Dynamics. Proceedings of the AIAA Guidance, Navigation, and Control Conference 2010.
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76. Dìaz-Aguillò, M., Grynagier, A., Rais, B., Hewitson, M., Hueller, M., Nofrarias, M., Ferraioli, L., Monsky, A., Armano, M., Lobo, A., & Garcìa, E. (2010, June). Modeling LISA Pathfinder for Data Analysis. Journal of Physics Conference Series, 8th International LISA Symposium.
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75. Saupe, F., Maurice, J.-B., King, F., & Fichter, W. (2009, August). Robustness Analysis of Linear Time Periodic Systems using Harmonic Transfer Function. Proceedings of the AIAA Guidance, Navigation, and Control Conference 2009.
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74. Maurice, J.-B., King, F., Fichter, W., Dieterich, O., & Konstanzer, P. (2009, September). Floquet Convergence Analysis for Periodic Active Rotor Systems Equipped with Trailing Edge Flaps. Proceedings of the 35th European Rotorcraft Forum.
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73. Böhm, C., Merk, M., Fichter, W., & Allgöwer, F. (2009). Spacecraft Rate Damping with Predictive Control using Magnetic Actuators Only. In K. Magni & F. Allgöwer (Eds.), Nonlinear Model Predictive Control - Towards New Challenging Applications, Lecture Notes in Control and Information Sciences (pp. 511–520). Springer.
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72. Ahmad, A., Del Bue, A., & Lima, P. (2009). Background Subtraction Based on Rank Constraint for Point Trajectories. 1–3.
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71. Ziegler, T., Fichter, W., Schulte, M., & Vitale, S. (2008, June). Principles, Operations, and Expected Performance of the LISA Pathfinder Charge Management System. Journal of Physics Conference Series, 7th International LISA Symposium.
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70. Trittler, M., Fichter, W., Voit-Nitschmann, R., Schmoldt, R., & Kittmann, K. (2008). Preliminary System Identification of the Blended Wing Body Flight Demonstrator VELA 2 from Flight Data.
Proceedings of the AIAA Atmospheric Flight Mechanics Conference and Exhibit 2008.
https://doi.org/10.2514/6.2008-6896
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69. Schleicher, A., Saage, R., Hirth, M., Brandt, N., & Fichter, W. (2008, June). Drag-Free Control Design for Misaligned Cubic Test Masses. Proceedings of the 7th International ESA Conference on Guidance, Navigation & Control Systems.
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68. Hirth, M., Fichter, W., Brandt, N., Schleicher, A., Gerardi, D., & Wanner, G. (2008, June). Optical Metrology Alignment and Impact on the Measurement Performance of the LISA Technology Package. Journal of Physics Conference Series, 7th International LISA Symposium.
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67. Brandt, N., & Fichter, W. (2008, June). Results and Consequences for the LISA Pathfinder Inertial Sensor FEM Analysis. Journal of Physics Conference Series, 7th International LISA Symposium.
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66. Ahmad, A., & Dhang, N. (2008). Probabilistic Roadmap Method and Real Time Gait Changing Technique Implementation for Travel Time Optimization on a Designed Six-legged Robot. 1–5.
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65. Ziegler, T., Göbel, M., Schleicher, A., & Fichter, W. (2007). Calibration of the Micro-Newton Propulsion System of the LISA Pathfinder Drag-Free Satellite. CEAS Conference, 1.
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64. Ziegler, T., & Fichter, W. (2007, August). Test Mass Stiffness Estimation for the LISA Pathfinder Drag-Free System. AIAA Guidance Navigation and Control Conference.
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63. Montemurro, F., Fichter, W., & Schlotterer, M. (2007, June). Sliding Mode Technique Applied to Test Mass Suspension Control. Proceedings of the 17th IFAC Symposium on Automatic Control in Aerospace.
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62. Fichter, W., Schleicher, A., Bennani, S., & Wu, S. (2007, August). Closed Loop Performance and Limitations of the LISA Pathfinder Drag-Free Control System.
Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit 2007.
https://doi.org/10.2514/6.2007-6732
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61. Well, K. H. (2006, August). Aircraft Control Laws for Envelope Protection. Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit 2006.
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60. Mayanna, A., Grimm, W., & Well, K. H. (2006, August). Adaptive Guidance for Terminal Area Energy Management (TAEM) of Reentry Vehicles. Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit 2006.
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59. Reber, D. Y., & Ayadi, W. (2005). Decoupling of an H-Infinity Controller in Observer Form for Helicopter Vibration Reduction. International Basic Research Conference on Rotorcraft Technology, 2.
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58. Erb, S. (2005). Optimization of a GTO-GEO Low Thrust Satellite Transfer under Industrial Considerations. SIAM Conference on Optimization.
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57. Ayadi, W., & Reber, D. Y. (2005). Helicopter Vibration Reduction Using Digitally Redesigned H-Infinity Controller in Observer Form. International Basic Research Conference on Rotorcraft Technology, 2.
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56. Wallner, E. M., & Well, K. H. (2004). Nonlinear Adaptive Flight Control for the X-38 Vehicle. Proceedings of the 18th International Symposium on Space Flight Dynamics (ESA SP-548), 353.
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55. Wallner, E. M., & Well, K. H. (2003). TETRA Technologien für zukünftige Raumtransportsysteme Anpassung der Lageregelung der X-38 an eine neue Version der Aerodynamik. AIAA Guidance, Navigation, and Control Conference.
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54. Kornienko, A., & Well, K. (2003, August). Estimation of Longitudinal Motion of a Remotely Controlled Airship. Proceedings of the AIAA Atmospheric Flight Mechanics Conference and Exhibit 2003.
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53. Grimm, W., Stäbler, T., Wallner, E., Wiegand, A., da Costa, R., Roenneke, A. J., & Ortega, G. (2003). Unified Guidance and Control for Planetary Entry. International Symposium on Atmospheric Reentry Vehicles and Systems, 3.
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52. Wallner, E., & Well, Klaus. H. (2002). Direct Adaptive Control of Aerospace Vehicles Using CMAC Neural Networks. Tagungsband DGLR Jahrestagung.
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51. Wallner, E., & Well, Klaus. H. (2002). Attitude Control of a Reentry Vehicle with Internal Dynamics. Proceedings of the AIAA Guidance, Navigation, and Control Conference 2002.
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50. Wallner, E., Gräßlin, M., Müller, S., Well, Klaus. H., Schoettle, U., Wagner, O., & Sachs, G. (2002). Development of Guidance and Control Algorithms for the X-38 Return Vehicle. Tagungsband DGLR Jahrestagung.
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49. Mannchen, T., & Well, Klaus. H. (2002). Influence of the Number of Rotor Blades on Helicopter Active Vibration Reduction Potential. Proceedings of the European Rotorcraft Forum, 28, Article 81.
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48. Mannchen, T., Bates, D. G., & Postlethwaite, I. (2002). Worst-Case Uncertain Parameter Combinations for Flight Control Systems Analysis. Proceedings of the IFAC World Congress, 15, Article 1210.
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47. Gräßlin, M., Wallner, E., Burkhardt, J., Schoettle, U., & Well, K. H. (2002). Adaptive Guidance and Control Algorithms Applied to the X-38 Reentry Mission. International Astronautical Congress.
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46. Wallner, E., & Well, Klaus. H. (2001, August). Nonlinear Flight Control Design for the X-38 Using CMAC Neural Networks. Proceedings of the AIAA Guidance, Navigation, and Control Conference 2001.
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45. Teufel, P., & Well, Klaus. H. (2001, June). Multidimensional Gust Simulation and Load Alleviation of a Flexible Aicraft. Proceedings of the IFASD Conference.
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44. Schubert, R. A., & Well, K. H. (2001). Flight Mechanical Modelling of an ″Air Train″ using Methods and Formalisms of Multibody Systems. Lighter-than-Air, 14.
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43. Mannchen, T., & Well, Klaus. H. (2001). Helicopter Vibration Reduction using Periodic Robust Control. Proceedings of the AIAA Guidance, Navigation, and Control Conference, AIAA-2001-4034.
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42. Hablowetz, T., Mannchen, T., & Well, Klaus. H. (2001). Advanced Helicopter Flight Simulation with Controller in the Loop. Proceedings of the European Rotorcraft Forum, Netherlands Congress Centre, 26, Article 25.
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41. Gath, P. F., & Well, K. H. (2001). Trajectory Optimization Using a Combination of Direct Multiple Shooting and Collocation. AIAA Guidance, Navigation, and Control Conference, AIAA-2001-4047.
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40. Fischer, D., Zöbelein, T., & Roenneke, A. (2001). Flugführung und Flugregelung des Deorbitmanövers von X-38/CRV. DGLR-Jahrbuch.
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39. Well, K. H., Ortega, G., Mehlem, K., Steinkopf, M., Mulder, J., & van der Boom, A. J. J. (2000, October). ESTEC Guidance, Navigation, and Control activities for the Crew Return Vehicle (CRV). ESA International Conference on Spacecraft Guidance, Navigation and Control Systems, ESTEC.
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38. Hablowetz, T. (2000). Advanced Helicopter Flight and Aeroelastic Simulation based on General Purpose Multibody Code. AIAA Modeling and Simulation Technologies Conference, AIAA 2000-4299.
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37. Gath, P. F., Well, Klaus. H., & Mehlem, K. (2000). Automatic Initial Guess Generation for Ariane 5 Dual Payload Ascent Trajectory Optimization. AIAA Guidance, Navigation, and Control Conference, AIAA 2000-4589.
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36. Teufel, P., Hanel, M., & Well, K. H. (1999, October). Integrated Flight Mechanic and Aeroelastic Modelling and Control of a Flexible Aircraft Considering Multidimensional Gust Input. Proceedings of the RTO AVT Specialists’ Meeting on “Structural Aspects of Flexible Aircraft Control”.
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35. Klotz, H., Starke, J., Frapard, B., Champetier, C., Grimm, W., & Strandmoe, S. E. (1999). Guidance, Navigation, and Control for Autonomous Reentry and Precision Landing of future small Capsules. AAF International Symposium on Atmospheric Reentry Vehicles and System.
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34. Klotz, H., Markus, M., Grimm, W., & Strandmoe, S. E. (1999). Guidance and Control for Autonomous Reentry and Precision Landing of a small Capsule. ESA International Conference on Spacecraft Guidance, Navigation, and Control, 4.
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33. Gath, P. F., & Calise, A. J. (1999). Optimization of Launch Vehicle Ascent Trajectories with Path Constraints and Coast Arcs. AIAA Guidance, Navigation, and Control Conference, AIAA-99-4308.
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32. Well, K. H. (1998). ARIANE V Ascent Trajectory Optimization with a First-Stage Splash-Down Constraint. IFAC Workshop, 8.
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31. Weirich, G., & Grimm, W. (1998). A Classical Approach Towards the Ascent Control of a Hypersonic Vehicle. Workshop Des SFB 255: Optimalsteuerungsprobleme von Hyperschall-Flugsystemen, Tagungsband, 51–62.
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30. Teufel, P., Hanel, M., & Well, K. H. (1998). Integrated Flight and Aeroelastic Control of a Flexible Transport Aircraft. AIAA Guidance, Navigation, and Control Conference and Exhibit, AIAA-98-4297.
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29. Grimm, W., & Well, Klaus. H. (1997, March). Intercept Maneuvers with Reduced Detection Probability. DERA, Farnborough.
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28. Paus, M., & Well, Klaus. H. (1996). Optimal Ascent Guidance for a Hypersonic Vehicle. AIAA Guidance, Navigation and Control Conference, AIAA 96-3901, 9.
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27. Roenneke, A. J., & Well, K. H. (1995). Nonlinear Flight Control for a High-Lift Reentry Vehicle. AIAA Guidance, Navigation, and Control Conference, AIAA 95-3370-CP, 1798–1805.
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26. Roenneke, A., Schütz, K., & Well, Klaus. H. (1995). Trajectory Optimization Using 6-DOF Vehicle Models. IFAC Workshop on Control Applications of Optimization, 10.
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25. Paus, M., Grimm, W., & Well, Klaus. H. (1995). Real-Time Optimization for the Guidance of Dynamic Systems. IFAC Workshop on Control Applications of Optimization, 10.
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24. Kämpf, B. G., & Well, Klaus. H. (1995). Attitude Control System for a Remotely-Controlled Airship. AIAA Lighter-than-Air Systems Technology Conference, 11.
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23. Figgen, A., Roenneke, A. J., & Well, Klaus. H. (1995). Investigations of Guidance and Control of a Semi-Ballistic Reentry Vehicle. Space Course, 3, 209–229.
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22. Jänsch, C., & H., W. K. (1994). Optimal Multi-Criteria Aeroassisted Orbital Transfer Trajectories. IFACS Symposium on Automatic Control in Aerospace, 13.
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21. Grimm, W. (1993). Optimal Flight Paths with Constrained Dynamic Pressure. In R. B. et al. (Ed.), Optimal Control - Calculus of Variations, Optimal Control Theory, and Numerical Methods (Vol. 111). Birkhäuser.
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20. Grimm, W. (1993). On Ascent Guidance of a Hypersonic Vehicle. IFAC-Symposium on Automatic Control in Aerospace Control, 12.
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19. Buhl, W., Ebert, K., Herbst, H., Schnepper, K., & Well, Klaus. H. (1993). Branched Trajectory Optimization for a Two-Stage to Orbit Vehicle. SIAM Conference on Numerical Analysis.
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18. Roenneke, A. J., & Well, Klaus. H. (1992). Reentry Control of a Low-Lift Maneuverable Spacecraft. AIAA Guidance, Navigation, and Control Conference, AIAA 92-4455-CP, 641–652.
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17. Paus, M. (1992). A General Approach to Optimal Real-Time Guidance of Dynamic Systems Based on Nonlinear Programming. AIAA Guidance, Navigation, and Control Conference, Article 92–4378.
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16. Cliff, E. M., Well, K. H., & Schnepper, K. (1992, January). Flight-Test Guidance for Airbreathing Hypersonic Vehicles.
Proceedings of the AIAA Guidance, Navigation and Control Conference 1992.
https://doi.org/10.2514/6.1992-4301
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15. Grimm, W., & Well, K. H. (1991). Optimal Guidance Anticipating Missile Performance. AGARD-Symposium of the Guidance and Control Panel on Air Vehicle Mission Co, 53.
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14. Grimm, W., Jänsch, C., Markl, A., Schnepper, K., & Well, K. H. (1991). Guidance of Aerospace Vehicles. Trajectory Optimization and Guidance of Aerospace Vehicles, Article DR 4.04 of the Carl-Cranz-Gesellschaft.
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