Fuzzy smooth switching algorithm for VSCMGs based on clustering-mutated PSO

Abstract:

Aiming at the conflict of the stationary and rapidness of the terminal mode switching when the variable speed control moment gyro is applied as the actuator on the agile remote sensing satellite for attitude maneuver, on the basis of considering the frame speed error, the attitude error parameter is designed as the switching index, the transition rule within the error parameter switching area is formulated, and the command torque is assigned to CMG and flywheel in real time and solved respectively. A control torque gyroscope/reaction flywheel fuzzy smooth switching control law is proposed. In order to make the attitude of the satellite at the end of attitude maneuver reach the requirements of attitude stability and pointing accuracy in a shorter time, the clustering variation improved particle swarm optimization algorithm is proposed to optimize the parameters of the control law and determine the best switching region and switching parameters. Finally, the simulation results show that the improved particle swarm optimization algorithm always shows better fitness than the traditional particle swarm optimization algorithm in the same iteration times, with faster convergence speed and higher convergence accuracy. Compared with the existing control law, the fuzzy smooth switching control law after parameter optimization can complete the smooth switching of dual modes in a shorter time. At the end of attitude maneuver, the requirements of attitude stability and pointing accuracy can be reached more quickly, and the control performance of agile maneuver and high stable pointing of remote sensing satellites can be improved, which raises the quality of imaging mission.