An Efficient Convex Optimization Pattern for Model Predictive Control of Hydraulic Servo Systems

The fast dynamic characteristic of hydraulic servo systems poses a great challenge to the physical implementation of model predictive control (MPC). To address the online iterative solving of the optimal control problem, this paper proposes an efficient convex optimization pattern to obtain the optimal control variables in the shortest possible control period, thus supporting the system tracking performance and safety. An optimal control problem of the hydraulic servo system MPC is established based on the considered mechanism model. The convexity of the optimization model is proved, which makes the global convergence valid to avoid complex solving. As a model transformation prerequisite, the positive definiteness of the Hessian matrix is elucidated. Then, a conversion method from the MPC quadratic programming form to the non-negative least squares form is presented, which enables simpler implementation programming and more efficient optimization solving. Finally, some numerical experiments verify the effectiveness and merits of the proposed pattern.