Barrier-Lyapunov-Based Adaptive Fuzzy Finite-Time Tracking of Pure-Feedback Nonlinear Systems With Constraints
Nan Wang, Zhumu Fu, Shuzhong Song, Tong Wang
Abstract
In this article, the finite-time adaptive fuzzy state-feedback tracking control problem for the pure-feedback system with full state constraints is studied. In order to transform the pure-feedback form into system strict-feedback case, the mean value theorem is introduced. By employing finite-time-stablelike function and state transformation for output tracking error, the output tracking error converges to a predefined set in a fixed finite interval. To tackle the problem of state constraints, integral barrier Lyapunov functions are utilized to guarantee that the state variables remain within the prescribed constraints with feasibility check. Fuzzy logic systems are utilized in this article to approximate nonlinear uncertainties. In addition, all the signals in the system are guaranteed to be semiglobal ultimately uniformly bounded. Finally, two simulation examples are given to show the effectiveness of the proposed control strategy.