Adaptive NNs backstepping fault control for a class of nonlinear systems

In this paper, the problem of fault-tolerant control (FTC) is investigated for a class of nonlinear single input and single output (SISO) systems in the non-strict feedback form. The considered system possess unknown nonlinear functions, measured states, unknown control direction and actuator faults (bias and gain faults). With the help of Neural Network System (NNs) to approximate the unknown nonlinear functions and a fuzzy adaptive observer is designed to estimate the unmeasured states. In the frame of adaptive backstepping design technique, and by combining with the nonlinear fault-tolerant control theory, the control performance of the closed-loop system is guaranteed by suitably choosing the design parameters, an adaptive NNs output feedback FTC method is developed. It is shown that the given control approach can prove that all signals in the closed-loop system are proved to be bounded, and the tracking errors between the system outputs and the reference signals converge to a small neighborhood of zero by choice of the design parameters.