Adaptive tracking control for a class of uncertain nonlinear systems with infinite number of actuator failures using neural networks

*Correspondence: [email protected] College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, Shandong 266510, P.R. China Abstract We consider adaptive compensation for infinite number of actuator failures in the tracking control of uncertain nonlinear systems. We construct an adaptive controller by combining the common Lyapunov function approach and the structural characteristic of neural networks. The proposed control strategy is feasible under the presupposition that the systems have a nonstrict-feedback structure. We prove that the states of the closed-loop system are bounded and the tracking error converges to a small neighborhood of the origin under the designed controllers, even though there are an infinite number of actuator failures. At last, the validity of the proposed control scheme is demonstrated by two examples.