A Novel Dynamic Event-Triggered Fuzzy Adaptive Prescribed-Time Tracking Control for Nonstrict Feedback Nonlinear Systems With Unknown Control Directions

Abstract

Control design for nonstrict feedback nonlinear systems (NSFNS) with nonlower triangular structure may encounter algebraic loop problem, which is a significant, challenging, yet complicate issue to develop a controller with unknown control directions, especially in the presence of external disturbances and time-varying parameters. To solve these issues, unlike existing studies on prescribed-time stability under unknown control directions, a novel zero-error prescribed-time tracking control scheme is proposed for NSFNS based on the fuzzy logic approximation and adaptive technique. Moreover, a new switching event-triggered mechanism that focuses on triggering strategies and conditions to minimize resource wastage from continuous controller sampling is constructed. This approach effectively reduces the frequency of sampling and energy loss within the controller. In addition, the boundedness of the Lyapunov function is analyzed using invariant set theory. It demonstrates that the tracking error converges to zero within a user-defined time, which simultaneously ensures all signals of the closed-loop system be bounded and Zeno-free phenomenon. Finally, the efficacy of the proposed control algorithm is validated through numerical simulation results.