Spacecraft Attitude Agile Maneuver Control Based on Reinforcement Learning
Aiming at the problems of uncertain model parameters and unknown external interference in the space-craft attitude agile maneuver task,a control method of sliding mode observer based on reinforcement learning combi-ning nonlinear interference observer is proposed.Firstly,the attitude dynamics model of the spacecraft was introduced.Secondly,reinforcement learning was used to solve the uncertainty of the moment of inertia of the system,and a sliding mode reaching law based on elastic energy function was designed to speed up the convergence speed of reinforcement learning and combine the nonlinear disturbance observer to estimate the unknown external interference.Finally,the simulation results show that the method can maintain high attitude tracking accuracy and strong robustness,to meet the requirements of space high dynamic target tracking control.
High dynamic attitude trackingReinforcement learningSliding mode observerElastic energy func-tion
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