Fault compensation-based adaptive tracking control for nonlinear systems with actuator saturation and multiple sensor faults

An adaptive tracking control scheme based on a multi-dimensional Taylor network(MTN) is proposed for nonlinear systems with multiple sensor faults and actuator saturation. This article utilizes a smooth hyperbolic tangent function to transform the non-smooth actuator saturation model into a smooth linear model, thus addressing the challenges posed by actuator saturation on the system. By applying a third-order absolute value Lyapunov function and incorporating it into the adaptive control design process, the estimation of fault losses and design of compensation coefficients are carried out to eliminate the effects of sensor faults. Experimental results demonstrate that the proposed controller can eliminate the impact of sensor faults and actuator saturation, ensuring that all signals in the closed-loop system remain within bounded ranges. Additionally, it can drive the tracking error to converge to a small region near the origin.