Agile satellite attitude optimal predictive control method based on Particle Swarm Optimization

Agile satellite is a typical multi-body nonlinear system, and there is a strong coupling between the state variables and the input control variables. In order to ensure the control precision of agile satellite attitude, an optimal predictive control method based on Particle Swarm Optimization (PSO-NIVIP() is proposed The attitude position and the angular velocity at the next moment are obtained by establishing the discrete attitude prediction equation. Then the Particle Swarm Optimization algorithm is used to optimize the optimization objective function of the combination of the predicted attitude error and the predicted control moment, so as to obtain the equilibrium solution satisfying the attitude error and the optimal control moment, and realize the real-time prediction and tolling optimization control of the satellite attitude. By comparing and analyzing the simulation results with the sliding mode control method, it can be seen that the PSO-NMPC can achieve large-angle stable maneuver around 19s and the attitude stability precision can reach 7e-04" under the condition of sustained unknown disturbance torque. It shows good maneuvering efficiency and stability.