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Abstract The solar system boundary exploration mission has the characteristics of long flight time, high fuel consumption, complex gravity-assist sequence and strict constraints. Therefore, the number of decision variables and the search space of the transfer trajectory are very large, resulting in poor convergence and efficiency of the global search of the metaheuristic algorithm. Moreover, the existing gravity assist space pruning algorithm is no longer applicable for solar system boundary exploration. To effectively reduce the search space and improve the effect of trajectory optimization, an improved gravity assist space pruning algorithm is proposed. In this algorithm, a unique pruning procedure is used to effectively prune the search space, a shape of solution space box bounds combining rectangle and rhombus is adopted, and a method to automatically determine the solution space box bounds is presented. To verify the effectiveness of the improved gravity assist space pruning algorithm, the sensitivity of pruning effect to parameters is analyzed and the optimization effects of three typical metaheuristics are compared. The optimization results of 50 repeated runs of the differential evolution algorithm in the entire search space and the solution space box bounds are compared. Simulation results show that the performance of differential evolution algorithm is better than bat algorithm and firefly algorithm. And the improved pruning algorithm can increase the efficiency of subsequent optimization by more than eleven times and the convergence probability of the objective function by fifty of times. The applicability and efficiency of the proposed method for the solar system boundary exploration are demonstrated.

The capture control of test mass by means of the electrostatic suspensions is crucial for drag-free spacecraft. The test mass must be released to the cage center of the inertial sensor accurately and quickly. This paper proposes a minimum-time capture control method for the test mass release phase of drag-free spacecraft. An analytical solution of optimal control is derived based on Pontryagin’s minimum principle and the linearized dynamics model of the test mass during the release phase. The parameters of the analytical solution are initially guessed with an approximate linear solution of the test mass dynamics model and are slightly modified by using differential correction. Compared with the exact numerical solution by the hp-adaptive pseudospectral method, the analytical solution is proved to be minimum-time. Numerical simulation shows that the proposed control method quickly captures the test mass to the cage center of the inertial sensor. The capture time to stabilization is only half that of the traditional controller.

This paper aims to propose a switching rule to improve the efficiency and stability of the mode switching process for the drag-free satellite. The switching rules will ensure the stability of the different controllers during the switching process. Unlike traditional satellite switching control, the inner loop and the outer loop of the drag-free satellite are strongly coupled. The drag-free satellite not only needs to consider the controller design in the inner loop but also the controller design of the outer loop. In the outer loop, a Proportion Integration Differentiation control method is adopted to design the controller. In the inner loop, considering the release error effect of the test mass, a nonlinear sliding-mode control is employed as a controller before the mode switch. The H∞ mixed-sensitivity controller, to improve the robustness of the system and solve the problem of controller saturation, is designed after the mode switch. In the stability analysis of the switching system, the piecewise continuous Lyapunov function method is adopted. The region of attraction, which is used as the switching rule, is calculated based on the sum of squares. The obtained results demonstrate that the proposed switching rule satisfies the control accuracy and system stability.

This paper proposes a robust control allocation for the capture control of the space inertial sensor’s test mass under overcritical conditions. Uncertainty factors of the test mass control system under the overcritical condition are analyzed first, and a 6-DOF test mass dynamics model with system uncertainty is established. Subsequently, a time-varying weight function is designed to coordinate the allocation of 6-DOF generalized forces. Moreover, a robust control allocation method is proposed to distribute the commanded forces and torques into individual electrodes in an optimal manner, which takes into account the system uncertainties. This method transforms the robust control allocation problem into a second-order cone optimization problem, and its dual problem is introduced to simplify the computational complexity and improve the solving efficiency. Numerical simulation results are presented to illustrate and highlight the fine performance benefits obtained using the proposed robust control allocation method, which improves capture efficiency, increases the security margin and reduces allocation errors.