Adaptive reduced-order K-filters based DSC of uncertain systems with input unmodeled dynamics and dead-zone

Using dynamic surface control method, an adaptive output feedback prescribed performance tracking control scheme is proposed for a class of uncertain nonlinear systems with input unmodeled dynamics and dead-zone in this paper. Reduced-order K-filters are designed to observe unmeasured states. Input dead-zone characteristic is considered on the basis of the control input having unmodeled dynamics. A normalization signal is employed to deal with the negative impact of nonlinear input unmodeled dynamics, and a transformation of tracking error is designed to implement constrained performance tracking control. The state unmodeled dynamics is described by Lyapunov function based on global exponential stability. By the theoretical analysis, the transient tracking performance is guaranteed, and the signals in the closed-loop system are proved to be semi-globally uniformly ultimately bounded. A numerical simulation example shows the effectiveness of the proposed approach.