Adaptive Stability Augmentation and Model Predictive Trajectory Tracking Control for Flight Systems
Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics
Final Report Abstract
The goal of this project was the development of control algorithms which allow for operation of unmanned aircraft systems even under severe degradation such as structural damage or actuator failure. Two main aspects to achieve this task were identified and subsequently investigated by the collaborating institutes. First, an inner-loop stabilizing controller which quickly adapts to plant parameter changes had to be designed. Second, an outer-loop trajectory tracking or path following controller had to be developed which accounts for the changing dynamics and constraints of the inner-loop controller. Towards the objective of the inner-loop controller, different adaptive augmentation strategies for a nonlinear baseline controller have been designed and successfully flown for propeller degradations. Importantly, design plant augmentation has been designed. Additionally, various control allocation strategies have been flight tested in the case of a total propeller loss thereby ensuring stabilization by utilizing maximum control power available. A novel control strategy referred to as so-called Incremental Control that increases the robustness of feedback linearization techniques was investigated additionally to the adaptive controller and showed surprisingly good results. Then, to achieve online parameter estimation, various methods including gradient descent, Lyapunov based concurrent learning and Kalman filter were used to estimate the drag coefficients and control effectiveness of the propellers to evaluate the available control power. To achieve realistic trajectories that the system can track, nonlinear reference models were successfully implemented along with linear reference models. Moreover, realistic limitations in signals ensures that achievable signals are tracked by the system for nominal conditions. In the case of actuator faults, the estimates of the control effectiveness were used to achieve the similar physical feasibility. An extension to the switching logic developed is to be further investigated. Mainly two different approaches for outer-loop design were pursued, both having in common the idea of applying real-time online optimization to handle the dynamical system’s constraints. First, a path following controller was designed which interprets the control goal purely geometrical and determines the speed of mission execution online. That unconventional approach to MAV position and velocity control promises good performance and a fast execution of missions where a path has to be traversed and the traversing speed may be chosen freely. Simulation results show favorable performance and straight-forward reconfigurability in case of plant degradation. As no explicit robustness guarantees could be provided for this approach, we also designed a Tube MPC controller for position tracking. Outside flight tests were successfully performed and also proved the real-time feasibility of the employed optimization algorithms. Encouraged by the positive results regarding practical applicability of optimization-based control to the problem of MAV control, we also designed a moving horizon estimation along an optimal control allocation for online control effectiveness determination and adaptation. In flight tests, a take-off with a single rotor degraded to only 5% effectiveness was successful.
Publications
- "lncremental Fault -Tolerant Attitude Controller of a Multicopter," in Workshop 'Fehlertolerante Steuerung von Multikoptern', Bochum, 2016
V. S. Akkinapalli, S. Saboo and F. Holzapfel
- „Adaptive Nonlinear Design Plant Uncertainty Cancellation for a Multirotor,“ in International Conference on Unmanned Aircraft Systems (ICUAS), 2016
V. S. Akkinapalli, P. Niermeyer, B. Lohmann und F. Holzapfel
(See online at https://doi.org/10.1109/ICUAS.2016.7502555) - „Geometric Path Following Control for Multirotor Vehicles Using Nonlinear Model Predictive Control and 3D Spline Paths,“ in International Conference on Unmanned Aircraft Systems (ICUAS), 2016
P. Niermeyer, V. S. Akkinapalli, M. Pak, F. Holzapfel und B. Lohmann
(See online at https://doi.org/10.1109/ICUAS.2016.7502541) - „A Control Effectiveness Estimator with a Moving Horizon Robustness Modification for Fault-Tolerant Hexacopter Control,“ in IFAC World Congress, Toulouse, 2017
P. Niermeyer, M. Pak und B. Lohmann
(See online at https://doi.org/10.1016/j.ifacol.2017.08.045) - „Fault Tolerant Incremental Attitude Control using Online Parameter Estimation for a Multicopter System,“ in Proceedings of the 25th Mediterranean Conference on Control and Automation, 2017
V. S. Akkinapalli, G. P. Falconi und F. Holzapfel
(See online at https://doi.org/10.1109/MED.2017.7984159) - „Onboard Multi-Rate Tube Model Predictive Position Control for a Hexacopter: From Design to Outdoor Flight Experiments,“ in 26th International Conference on Information, Communication and Automation Technologies (ICAT), Sarajevo, Bosnia and Herzegovina, 2017
P. Niermeyer, M. Herb und B. Lohmann
(See online at https://doi.org/10.1109/ICAT.2017.8171596) - „Onboard Tube Model Predictive Control zur Positionsregelung eines Hexacopters: Auslegung und Flugexperimente,“ in GMA-Workshop: Theoretische Verfahren der Regelungstechnik, Anif, Österreich, 2017
P. Niermeyer
- „Smooth Path-Generation Around Obstacles Using Quartic Splines and RRTs,“ in IFAC World Congress, Toulouse, 2017
F. Janjoš, R. Reichart und P. Niermeyer
(See online at https://doi.org/10.1016/j.ifacol.2017.08.1708) - „Incremental Dynamic Inversion based Velocity Tracking Controller for a Multicopter System,“ in 2018 AIAA Guidance, Navigation, and Control Conference, 2018
V. S. Akkinapalli und F. Holzapfel
(See online at https://doi.org/10.2514/6.2018-1345)
