PSO-BP Tuned PID for CubeSat Attitude Control
摘要
With the continuous development of CubeSat technology from low earth orbit missions to deep space exploration missions, the demand for on-orbit autonomous control has intensified due to the constraints of limited power consumption and low data transmission rates. Proportional–integral–derivative (PID) parameters tuning is one of the key factors for achieving on-orbit autonomous control in CubeSats. Thus, in this study, a particle swarm optimization (PSO) and back propagation neural network tuning method for PID control (PSO-BP-PID) is proposed, and applied to the ICUBE-Q satellite model, a representative model used for CubeSat lunar missions. A series of simulation results demonstrate that the proposed method effectively reduces the overshoot and the steady-state error in the CubeSat attitude adjustment process under initial disturbance that occurs from the satellite deployment. Additionally, under sudden attitude disturbances during adjustment, the PSO-BP-PID can recalibrate the initial weight values to further optimize the control performance.