Command filter-based fuzzy adaptive nonlinear sensor-fault tolerant control for a quadrotor unmanned aerial vehicle

In this paper, a novel asymptotic fuzzy adaptive nonlinear fault tolerant control (FTC) scheme is presented for the under-actuated dynamics of a quadrotor unmanned aerial vehicle (UAV) subject to diverse sensor faults. The proposed FTC approach can deal with both additive sensor faults (bias, drift, loss of accuracy) and multiplicative sensor fault (loss of effectiveness). The overall dynamics is separated into position loop and attitude loop for FTC controllers design. Combining uncertain parameters and external disturbances, the four types of faults occurring in velocity sensors and Euler angle rate sensors are transformed equivalently into the unknown nonlinear function vectors and uncertain control gains. Fuzzy logic systems are used to approximate the lumped nonlinear functions, and adaptive parameters are estimated online. Nussbaum technique is introduced to deal with the unknown control gains. For both control loops, FTC controllers are designed via command filter-based backstepping approach, in which sliding mode control is introduced to establish asymptotic stability. All tracking error signals of the closed-loop control system are proved to converge to zero asymptotically. Finally, simulation comparisons with other methods demonstrate the effectiveness of the proposed FTC approach for quadrotor UAV with sensor faults.