Fault-Tolerant Control of Nonlinear Multiplayer Pursuit-Evasion Game With Actuator Faults

This article explores the issue of fault-tolerant optimal pursuit strategies in a nonlinear pursuit-evasion (PE) game involving multiple pursuers and a single evader. The main challenge lies in ensuring the successful capture of the evader despite the presence of actuator partial loss of effectiveness and bias faults within the pursuers group. To overcome this challenge, a two-layer control architecture is proposed. At the control layer, an integral sliding-mode controller is developed to mitigate the impact of bias faults, and an adaptive estimation mechanism is incorporated to identify the fault parameters. At the decision-making layer, performance index functions for both the pursuers and the evader are formulated based on the PE state error and their respective control strategies, and optimal pursuit and evasion strategies are derived by solving the associated Hamilton–Jacobi–Isaacs (HJI) equations. Furthermore, adaptive dynamic programming (ADP) is employed, with each participant using a critic network to approximate the optimal strategies for the pursuers and the evader. The proposed control mechanism is theoretically proven to ensure that all closed-loop signals remain uniformly ultimately bounded, allowing the faulty pursuers to successfully capture the evader. Finally, the effectiveness of the approach is validated through two simulation examples.