Optimal fault-tolerant control of reusable launch vehicle with actuator faults using zero-sum differential game theory

Abstract

Due to the harsh conditions and the potential for system faults and disturbances, ensuring the reliability and stability of reusable launch vehicles (RLVs) during reentry is critical. Traditional control strategies often struggle to maintain performance in the face of actuator faults and unpredictable external disturbances. In this paper, a novel approach for optimal fault-tolerant control in the attitude control system of reusable launch vehicle in reentry phase is introduced. This approach incorporates the zero-sum differential game theory to effectively address faults in actuators and external disturbance. We represent these actuator faults and external disturbance as an unpredictable bias in opposition to the control mechanism. By solving the Hamilton-Jacobi-Isaacs (HJI) equation and employing the Nash-Pontryagin minimax principle, we derive both the optimal control strategy and the maximum limit for the bias signal, thus attaining a Nash equilibrium saddle point. The estimation of the ideal cost function in real-time is executed via an adaptive critic neural-network, which utilizes adaptive dynamic programming method to formulate an adaptive control strategy. This method guarantees the stability and accuracy of the tracking performance, as well as the confinement of error margins within the attitude management system. Simulation results validate the efficacy of our proposed strategy for fault-tolerant control.