LAUSR

This letter proposes an Active Fault Tolerant Control (AFTC) framework for a quadcopter Unmanned Aerial Vehicle (UAV). The proposed framework is capable of achieving trajectory tracking, estimating states, as well as estimating and compensating for all four actuators multiplicative faults. The framework combines two optimization-based nonlinear estimation and control techniques; Nonlinear Moving Horizon Estimation (NMHE) and Nonlinear Model Predictive Control (NMPC). We formulate the NMHE algorithm such that it simultaneously estimates the states and the 4 actuators faults. These estimates are then provided to NMPC to achieve fault accommodation. To validate our proposed framework, we investigate two fault scenarios, where 4 actuators experience an abrupt and time-varying partial Loss Of Effectiveness (LOE) in the presence of noisy measurements. Finally, simulation results show satisfactory performance and prove that the proposed framework is numerically tractable and real-time applicable.