Adaptive Fuzzy Asymptotic Tracking Control of Uncertain Nonlinear Systems With Full State Constraints

This paper addresses the problem of adaptive constraint control for a class of uncertain nonlinear strict-feedback systems with full state constraints. Novel fuzzy logic-based adaptive adjustment techniques are adopted to help identify system uncertainties and unknown control coefficients. Then, a newly proposed nonlinear filter with adaptive parameter adjustment is employed to remove the complex calculation problem caused by repeated differentiation in the backstepping control design procedure. At the same time, the controller is constructed under the consideration that the state contains are not violated. Through the barrier Lyapunov theory analysis, the results that the system output signal tracks the desired trajectory and the tracking error converges to zero asymptotically are obtained. Finally, the numerical results of the comparative simulation verify the feasibility of the established control method.