Event‐triggered prescribed performance adaptive fuzzy asymptotic tracking of nonstrict‐feedback nonlinear systems

Abstract This paper considers the performance‐guaranteed event‐triggered adaptive asymptotic tracking control problem for nonstrict feedback nonlinear systems with uncertain external disturbances. More precisely, the upper bounds of control gain function in stability analysis are eliminated by establishing Lyapunov function with lower bounds of control coefficients. Compared with the previous guaranteed performance results where the tracking errors converge to the neighborhood of the origin, the control scheme proposed in this paper ensures that the tracking error asymptotically converges to zero by constructing the smooth functions and boundary estimation method. So that the prescribed performance of the system is always achieved. In addition, the event‐triggered strategy is developed to reduce the waste of communication resources. The proposed control law can ensures that all the signals of system are bounded. Meanwhile, the Zeno behavior can be effectively avoid. Finally, two examples are provided to prove the effectiveness of the proposed scheme.