Adaptive Fuzzy Asymptotic Tracking for Nonlinear Nonstrict-feedback Systems With Input Quantization

Abstract

This article investigates an adaptive fuzzy tracking control problem for the nonlinear nonstrict-feedback systems with quantized input. The control signal has a new transformation since a time varying auxiliary signal and a hyperbolic tangent function are introduced to the controller. Moreover, a novel adaptive fuzzy control scheme is proposed such that input quantization can be solved by applying hysteresis quantizer in the case of unknown quantization parameters. For traditional adaptive quantization control schemes with nonstrict-feedback form, current studies have shown that the tracking error can only converge to a small neighborhood of the origin. Based on the proposed control method, all the signals in the closed-loop system are bounded, and the tracking error can converge to zero asymptotically. Finally, the effectiveness of the presented method is shown via the numerical simulation results.