journal article·2020-12-07Open access

Trajectory/Path-Following Controller Based on Nonlinear Jerk-Level Error Dynamics

Patrick Piprek, Michael M. Marb, Pranav Bhardwaj, Florian Holzapfel

Applied Sciences· Volume 10· Issue 23

Abstract

This study proposes a novel, nonlinear trajectory/path-following controller based on jerk-level error dynamics. Therefore, at first the nonlinear acceleration-based kinematic equations of motion of a dynamic system are differentiated with respect to time to obtain a representation connecting the translation jerk with the (specific) force derivative. Furthermore, the path deviation, i.e., the difference between the planned and the actual path, is formulated as nonlinear error dynamics based on the jerk error. Combining the derived equations of motion with the nonlinear error dynamics as well as employing nonlinear dynamic inversion, a control law can be derived that provides force derivative commands, which may be commanded to an inner loop for trajectory control. This command ensures an increased smoothness and faster reaction time compared to traditional approaches based on a force directly. Furthermore, the nonlinear parts in the error dynamic are feedforward components that improve the general performance due to their physical connection with the real dynamics. The validity and performance of the proposed trajectory/path-following controller are shown in an aircraft-related application example.
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Research context

OpenAlex topics: Robotic Path Planning Algorithms · Vehicle Dynamics and Control Systems · Dynamics and Control of Mechanical Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Flight System Dynamics, Technical University of Munich, 85748 Garching, Germany

References (22)

Show source-provided references
1. Stevens, B.L., Lewis, F.L., and Johnson, E.N. (2016). Aircraft Control and Simulation: Dynamics, Controls Design, and Autonomous Systems, Wiley. [3rd ed.].10.1002/9781119174882 ↗
2. Sampling-Based Robot Motion Planning: A Review10.1109/ACCESS.2014.2302442 ↗
3. A Review of Motion Planning for Highway Autonomous Driving10.1109/TITS.2019.2913998 ↗
4. Unmanned Aerial Vehicle Path Following: A Survey and Analysis of Algorithms for Fixed-Wing Unmanned Aerial Vehicless10.1109/MCS.2013.2287568 ↗
5. A Survey of Path Following Control Strategies for UAVs Focused on Quadrotors10.1007/s10846-019-01085-z ↗
6. Falconi, G.P., and Holzapfel, F. (2014, January 13–14). Position tracking of a hexacopter using a geometric backstepping control law—Experimental results. Proceedings of the 2014 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology, Yogyakarta, Indonesia.10.1109/ICARES.2014.7024375 ↗
7. An Adaptive Three-Dimensional Nonlinear Path following Method for a Fix-Wing Micro Aerial Vehicle10.5772/53615 ↗
8. Schatz, S.P., and Holzapfel, F. (2014, January 13–14). Modular trajectory/path following controller using nonlinear error dynamics. Proceedings of the ICARES 2014, Yogyakarta, Indonesia.10.1109/ICARES.2014.7024374 ↗
9. Schatz, S.P., Schneider, V., Karlsson, E., Holzapfel, F., Baier, T., Dorhofer, C., Hochstrasser, M., Gabrys, A., Krause, C., and Lauffs, P.J. (2016, January 13–15). Flightplan flight tests of an experimental DA42 general aviation aircraft. Proceedings of the 2016 14th International Conference on Control, Automation, Robotics & Vision, Phuket, Thailand.10.1109/ICARCV.2016.7838646 ↗
10. Schatz, S. (2018). Development and Flight-Testing of a Trajectory Controller Employing Full Nonlinear Kinematics. [Ph.D. Thesis, Technische Universität München].
11. Bhardwaj, P., Raab, S.A., Zhang, J., and Holzapfel, F. (2019, January 17–21). Thrust command based Integrated Reference Model with Envelope Protections for Tilt-rotor VTOL Transition UAV. Proceedings of the AIAA Aviation 2019 Forum, Dallas, TX, USA.10.2514/6.2019-3266 ↗
12. Raab, S.A., Zhang, J., Bhardwaj, P., and Holzapfel, F. (2019, January 17–21). Consideration of Control Effector Dynamics and Saturations in an Extended INDI Approach. Proceedings of the AIAA Aviation 2019 Forum, Dallas, TX, USA.10.2514/6.2019-3267 ↗
13. Effect of Jerk and Acceleration on the Perception of Motion Strength10.2514/1.33757 ↗
14. Kyriakopoulos, K.J., and Saridis, G.N. (1988, January 24–29). Minimum jerk path generation. Proceedings of the 1988 IEEE International Conference on Robotics and Automation, Philadelphia, PA, USA.
15. Schneider, V., Piprek, P., Schatz, S.P., Baier, T., Dorhofer, C., Hochstrasser, M., Gabrys, A., Karlsson, E., Krause, C., and Lauffs, P.J. (2016, January 13–15). Online trajectory generation using clothoid segments. Proceedings of the 2016 14th International Conference on Control, Automation, Robotics & Vision, Phuket, Thailand.10.1109/ICARCV.2016.7838711 ↗
16. Schneider, V. (2018). Trajectory Generation for Integrated Flight Guidance. [Ph.D. Thesis, Technische Universität München].
17. Diaz-Mercado, Y., Lee, S.G., Egerstedt, M., and Young, S.Y. (2013, January 5–10). Optimal trajectory generation for next generation flight management systems. Proceedings of the IEEE/AIAA 32nd Digital Avionics Systems Conference (DASC), East Syracuse, NY, USA.10.1109/DASC.2013.6712566 ↗
18. Smooth Sub-Optimal Trajectory Generation for Transition Maneuvers10.1109/ACCESS.2020.2982231 ↗
19. Piprek, P., Gros, S., and Holzapfel, F. (2019). Rare Event Chance-Constrained Optimal Control Using Polynomial Chaos and Subset Simulation. Processes, 7.10.3390/pr7040185 ↗
20. Piprek, P., Gros, S., and Holzapfel, F. (2019, January 3–5). A Distributed Robust Optimal Control Framework Based on Polynomial Chaos. Proceedings of the 5th CEAS Specialist Conference on Guidance, Navigation & Control, Milano, Italy.
21. Three-Dimensional A* Dynamic Mission Planning for an Airborne Launch Vehicle
22. Enhanced Kinematics Calculation for an Online Trajectory Generation Module10.1016/j.trpro.2018.02.028 ↗