Fixed-Time Zero-Sum Pursuit-Evasion Game Control of Multisatellite via Adaptive Dynamic Programming

Inspired by the combination of zero-sum game and fixed-time convergence, this study investigates the optimal control strategy for a multisatellite fixed-time pursuit-evasion zero-sum game. A novel fixed-time adaptive dynamic programming approach is proposed to achieve satellite pursuit within a fixed time frame. The optimal control strategy for achieving Nash equilibrium of pursuit and target satellites' states is obtained. The derivation of the capture conditions in the game involves the construction of a Lyapunov function. Furthermore, a neural network weight update law is designed to eliminate the persistent excitation condition. In addition, this article employs a single network architecture, which simplifies the computing cost and complexity of the design process. Finally, the effectiveness of the proposed method is demonstrated through two simulation examples.