Performance-driven intelligent fault-tolerant control for unknown nonlinear systems

Abstract

This article investigates the fault-tolerant tracking control problem for the unknown nonlinear system subject to actuator faults and external disturbances. A novel performance-driven intelligent fault-tolerant controller is proposed, enabling accurate state tracking without requiring any estimation of system or fault dynamics. By integrating the prescribed performance control (PPC) framework with adaptive dynamic programming, the developed controller ensures that both transient and steady control performances satisfy predefined specifications while reducing the overall control cost. Notably, the conventional requirement in PPC designs that initial tracking errors lie within prespecified bounds is relaxed via a two-step mapping mechanism. Rigorous Lyapunov-based stability analysis guarantees that all closed-loop signals are uniformly ultimately bounded. The effectiveness of the proposed method is demonstrated through two simulation studies, including one on permanent magnet synchronous motor, which illustrates its potential for real-world industrial applications involving complex nonlinear dynamics and uncertain environments.