Adaptive Fault-Tolerant Tracking Control of Quadrotor UAVs against Uncertainties of Inertial Matrices and State Constraints

This paper presents a study on quadrotor unmanned aerial vehicle (UAV) fault-tolerant control scheme. According to the attitude model and safety of aircraft under uncertainty inertial matrix, state constraint by reinforcement learning is designed ensure safety. Even if boundary crossed, it can be pulled back means penalty function with learning. Meanwhile, in order inhibit oscillation caused immediate reward as usual, an adaptive update law proposed. Furthermore, considering coupled actuator fault system input saturation due Nussbaum-type utilized this work handle challenge, which likely causes singularity inertia matrix. As consequence, combined Lyapunov stability theory, confirmed that proposed FTC scheme ensures all closed-loop signals are bounded. Simulation results carried out illustrate effectiveness advantage