Adaptive Control of a Quadcopter in the Presence of large/complete Parameter Uncertainties

Adaptive control of unmanned aerial vehicles has gained recent interest in the field of flight control. Control algorithms seek to provide robustness in the presence of uncertain parameters, unmodeled dynamics, external disturbances or failure situations. As adaptive control algorithms are a priori designed to account for uncertain system dynamics and determine the system parameters online they provide a promising approach to improve the robustness of the control system w.r.t. parameter uncertainties. In this paper, we present an adaptive attitude controller for a quadcopter utilizing the full dynamic bandwidth of the system. The concept of Model Reference Adaptive Control is used in combination with a nonlinear control structure based on the method of nonlinear, dynamic inversion. Standard robustness modifications are used and adapted to the specific application on the quadcopter in order to ensure long term stability and robustness against unmodeled dynamics as well as external disturbances without persistent excitation. The focus is fast and robust adaption, so that even complete resets of the adaptive system in flight are possible. Further issues like unbounded growth of adaptive gains or integrator wind-ups due to actuator limitations are accounted for in the control structure and are successfully prevented. A small quadcopter is used as experimental platform, which enables the authors to perform real flight experiments without the need for expensive flight tests on larger systems. Therefore, all algorithms are optimized to run at high update rates on the onboard microprocessor hardware. The fast update rates of 1 kHz of the control loops are one key feature to achieve the high performance of the system. The tools based on MATLAB/Simulink to design the control system, the implementation and the optimization for the onboard hardware are presented as well as the quadcopter itself. Experimental results prove that a highly adaptive control system is able to handle a wide variety of external disturbances or parameter changes. To show the capabilities and verify the controller design, flight test results are presented for the following three extreme failure and uncertainty conditions: 1. Simulated power loss of a certain motor; 2. Disturbance due to external weight hung on a quadrocopter arm and cut off during flight; 3. Complete gain resets to zero during flight. The experimental results show that the adaptive controller can adjust fast enough to maintain stability and restore a desired transient performance under these adverse conditions. The presented adaptive control system and the implementation on the quadcopter and its microprocessor hardware using the simple MATLAB/Simulink framework is a starting point for ongoing research and development of adaptive algorithms on Micro Aerial Vehicles. It enables one to perform low cost validation of control algorithms in real flight experiments without the need for intense knowledge of programming languages or hardware design.