Research on Position Tracking Control of Pneumatic System based on Model Predictive Control

In order to solve the problem that the control effect of conventional model predictive control (MPC) becomes worse when the air pressure of pneumatic system changes, an adaptive model predictive control (AMPC) for pneumatic system is designed. Firstly, aiming at the problem that the conventional pneumatic system mathematical model considers less about the change of air pressure, the working principle of the pneumatic system is analyzed, and the Multiple Input and Single Output (MISO) mathematical model of the pneumatic system is established. Secondly, based on this model, MPC controller is designed to compare the influence of different prediction time domain (Np) and different air pressure on the control effect. Finally, in order to improve the response speed and reduce the system overshoot, an adaptive strategy is designed to adjust the prediction time domain according to the system error and the change of air pressure, thus an AMPC controller is designed. The simulation results show that AMPC controller can control the pneumatic system for faster and more stable position tracking, and when the air pressure changes, it can also make parameter adjustments to optimize the robustness and tracking performance of the system.