Abstract: The relative motion orbit control of spacecraft adopts sliding mode control, which has good anti-disturbance performance, but the parameter setting is complicated. In order to be close to engineering reality, the fuel optimization constraint and optimization algorithm were introduced, and a parameter-based autonomous optimization sliding mode control that comprehensively considers time, fuel consumption and errors was proposed. Firstly, based on the linear relative motion equation and exponential approach sliding mode control, the relative motion sliding mode controller model was established, and the energy-optimized trajectory planner gave the convergence constraint time to achieve efficient maneuvering. Secondly, the constraints of the sliding mode control adjustable parameters，time and error in the device were analyzed, and parameter magnitude optimization rules were formulated. Finally, through inertia weight improved particle swarm algorithm, the least fuel consumption within the allowable error range was used as the optimization evaluation standard, and the output was the combination of superior level and coefficient control parameters. Thus the optimal control of sliding mode was realized. The simulation shows that: using the parameter combination obtained by the particle finder, the sliding mode deviation controller can make the position and velocity errors converge stably through the minimum fuel consumption within specified time, increasing the spacecraft's life in orbit.

Key words: autonomous orbit change, sliding mode control, particle swarm algorithm, fuel optimization, autonomous optimization