Fuzzy Adaptive Fixed-Time Output Feedback Tracking Control for Stochastic Nonlinear Systems With Unmodeled Dynamics
Ze Ai, Huanqing Wang, Ben Niu, Xudong Zhao
Abstract
This article proposes an adaptive fixed-time output feedback tracking control scheme for a class of nonstrict- feedback stochastic nonlinear systems subjected to unmodeled dynamics and dynamic disturbances. To address the uncertainty arising from nonlinear terms, fuzzy logic systems (FLSs) are used as a universal approximator. Moreover, a state observer is utilized to estimate the unmeasured states. Then, the dynamic signal is introduced into the design process of the controller to solve unmodeled dynamics. Through stability analysis, the proposed new output feedback tracking controller guarantees the boundedness of all the signals, and the tracking error converges to a small residual set within a fixed time. The results of the simulation illustrate the effectiveness of the developed controller.