This paper studies the orbital pursuit-evasion-defense problem with the continuous low thrust propulsion. A control strategy for the pursuer is proposed based on the fuzzy comprehensive evaluation and the differential game. First, the system is described by the Lawden’s equations, and simplified by introducing the relative state variables and the zero effort miss (ZEM) variables. Then, the objective function of the pursuer is designed based on the fuzzy comprehensive evaluation, and the analytical necessary conditions for the optimal control strategy are presented. Finally, a hybrid method combining the multi-objective genetic algorithm and the multiple shooting method is proposed to obtain the solution of the orbital pursuit-evasion-defense problem. The simulation results show that the proposed control strategy can handle the orbital pursuit-evasion-defense problem effectively.

The open circuit voltage (OCV) and model parameters are critical reference variables for a lithium-ion battery management system estimating the state of charge (SOC) accurately. However, the polarization effect reduces the accuracy of the OCV test, and the model parameters coupled to the polarization voltage increase the non-linearity of the cell model, all challenging SOC estimation. This paper presents an OCV curve fusion method based on the incremental and low-current test. Fusing the incremental test results without polarization effect and the low current test results with non-linear characteristics of electrodes, the fusion method improves the OCV curve’s accuracy. In addition, we design a state observer with model parameters and SOC, and the unscented Kalman filter (UKF) method is employed for co-estimation of SOC and model parameters to eliminate the drift noise effects. The SOC estimation root mean square error (RMSE) of the proposed method achieves 0.99% and 1.67% in the pulse constant current test and dynamic discharge test, respectively. Experimental results and comparisons with other methods highlight the SOC estimation accuracy and robustness of the proposed method.

This paper studies the orbital pursuit-evasion problem with imperfect information, including measurement noise and input delay. The presence of imperfect information will degrade the players’ control performance and lead to mission failure. To solve this problem, a compensation control strategy for the players is proposed. The compensation control strategy consists of two parts: the guaranteed cost strategy and the time delay compensation method. First, a near-optimal feedback strategy called guaranteed cost strategy with perfect information is proposed based on a Lyapunov-like function and matrix analysis theory. Second, a time delay compensation method based on an uncertainty set is proposed to compensate for delayed information. The compensation control strategy is derived by combining the time delay compensation method with the guaranteed cost strategy. While applying this strategy to the game, the input of the strategy is generated by processing the measured data with the state estimation algorithm based on the unscented Kalman filter (UKF). The simulation results show that the proposed strategy can handle the orbital pursuit-evasion problem with imperfect information effectively.