失效卫星姿态接管的并行学习合作博弈控制

Taking the control constraint of microsatellites into consideration, this paper studies the cooperative game strategy learning and coordinated control problems of multiple microsatellites cooperatively taking over the attitude movement of a failed satellite. The cooperative game model of microsatellites is first established, providing the explicit expression of the Pareto optimal strategy that can handle the control constraint of microsatellites. Secondly, to learn the Pareto optimal strategy of microsatellites, we design a concurrent learning based Policy Iteration (PI) method free of the Persistency of Excitation (PE) condition by concurrent use of the past and current data. The condition that the used past data needs to satisfy to ensure the convergence of the Neural Network (NN) weight estimations is proposed, and the Uniform Ultimate Boundedness (UUB) of NN weight estimation errors is analyzed using the Lyapunov method. Then, the Pareto optimal strategy of microsatellites is approximated using the concurrent learning PI method. The obtained cooperative game strategy of microsatellites has a feedback control form, and after the NN weight learning is accomplished, the closed-loop coordinated control of microsatellites can be realized during the takeover control through independent game strategy calculation. Since the need of torque allocation required by traditional attitude control methods is avoided, the computational complexity of the method is independent of the number of microsatellites. Finally, numerical simulations are conducted to validate the effectiveness of the developed method.