SMS‐Based Event‐Triggered Fault Tolerant Control of Nonlinear Systems Using Adaptive Dynamic Programming

ABSTRACT An adaptive dynamic programming (ADP)‐based fault‐tolerant control (FTC) scheme integrating a sliding mode surface (SMS) and an event‐triggered mechanism is developed for a class of nonlinear systems with unknown actuator faults. A fault estimation observer is constructed, and its outputs are embedded into a formulated performance index, thereby recasting the FTC problem as a tractable optimal control problem. Within the resulting ADP framework, a controller is synthesized that automatically delivers active and optimal fault compensation. In place of conventional actor‐critic neural network (ACNN) architectures, a simplified critic‐only neural network (NN) is adopted, together with policy iteration, to solve the associated Hamilton–Jacobi–Bellman (HJB) equation. This structure substantially reduces computational complexity and enhances online applicability. CNN weights are updated via gradient descent combined with experience replay, which obviates the need for the persistent excitation condition that is often difficult to maintain in real‐time operation. Moreover, the proposed SMS‐based event‐triggering mechanism achieves better communication efficiency and improved closed‐loop performance relative to conventional state‐dependent triggering schemes. Theoretical analysis rigorously establishes the stability and convergence properties of the overall control system, while simulation experiments validate its practical effectiveness.