Fault-Tolerant Quadcopter Control Integrating Dynamic Equilibrium Analysis and Nonlinear Model Predictive Control

This study proposes a novel fault-tolerant control strategy for a quadcopter by integrating dynamic equilibrium analysis with nonlinear model predictive control (NMPC). First, we formulate an optimization problem based on dynamic equilibrium analysis. The feasibility of maintaining a constant altitude under a fault condition is determined by solving this problem. This analysis yields an optimal target that minimizes yaw angular velocity, while satisfying physical limitations. The target then serves as an online-updated reference for NMPC. This integrated approach enables a single controller to manage various rotor faults with a single fixed set of controller weights. Furthermore, the controller explicitly handles angular velocity constraints within the sensor limits, enhancing its reliability in a real quadcopter. The effectiveness of this strategy is verified through numerical simulations using a model based on an actual quadcopter, which enables visualization of operational bounds for various fault conditions. Simulations also demonstrate that stable flight can be achieved, while satisfying constraints even after a severe rotor fault.