Adaptive Fuzzy Control for Nonlinear State Constrained Systems With Input Delay and Unknown Control Coefficients

In this paper, an adaptive fuzzy controller is investigated for a class of strict-feedback nonlinear state constrained systems with both input delay and unknown control coefficients. Nussbaum gain technique is employed in the design progress to deal with the unknown time-varying control coefficients. Pade approximation and an intermediate variable are applied to compensate for the effect of the input delay and the barrier Lyapunov functionals (BLFs) are used to guarantee the states to remain within their constraint sets. The unknown functions are approximated by Fuzzy logic systems (FLSs). It is proved that the tracking error can converge to a compact set of the origin without violating the state constraint, and all closed loop signals remain bounded. The effectiveness of the proposed controller is illustrated through two examples.