Space Target Surveillance Based on Non-linear Model Predictive Control

Space target surveillance plays an important role in maintaining space advantages. Trajectory planning and attitude control are the key technologies of space target surveillance. We propose a nonlinear model predictive control framework to plan the trajectory of the surveillance satellite, track the surveillance target and keep a certain distance. In particular, the orbit dynamics and environmental disturbance of surveillance satellite are taken into account. A MatLab based real-time nonlinear model predictive control toolbox is used to solve these problems. The toolbox uses an efficient numerical method to calculate the maneuvering solution of MPC, which means that it allows the prediction horizon length to be greatly extended and save calculation time. The developed controller is simulated in a simulation scene, including the interference of near ground environment. We show that the proposed MPC method can be successfully applied to the satellite orbit planning and attitude control and the MATMPC toolbox can greatly speed up the solution of MPC optimization functions.