Adaptive neural network fixed‐time control of p$$ p $$‐normal systems with asymmetric output constraints

Abstract

AbstractThis paper studies the problem of fixed‐time control for a class of nonlinear ‐normal systems with asymmetric output constraints and external disturbances. Compared with the existing fixed‐time control schemes, the smooth switching functions are designed to avoid the singularity problem. Then, a time‐varying nonlinear transformation function (NTF) is introduced, blue and a unified tool to deal with the symmetric, asymmetric, and even unconstrained problems simultaneously. Moreover, by adding blue one power integration technology, the controller is designed, which can inhibit the influence of external disturbances on the system. According to Lyapunov stability analysis, the presented fixed‐time blue control method ensures that all signals are bounded in a fixed time. In the end, two simulation examples demonstrate the effectiveness of the proposed scheme.