Explicit model predictive control of permanent magnet synchronous motors based on multi-point linearization

Permanent magnet synchronous motors (PMSMs) have been broadly applied in servo-drive applications. It is necessary to improve the performance of PMSM. An explicit controller designed for PMSM based on multi-point linearization is proposed to reduce the linearized model error caused by different running status of PMSM. The mathematical model of PMSM system in the synchronous rotating frame and the problem formulation are introduced at first. Then, the preliminaries about explicit model predictive control (MPC) algorithm are presented in this article. Based on this, the multi-point linearization model is created for explicit MPC controller design. Moreover, the block diagram of the proposed method for PMSM system is presented. Finally, the simulation results are provided to demonstrate that the proposed explicit MPC controller based on multi-point linearization achieves better performance than that based on traditional single-point linearization, but requires the same online computation time because of the offline optimization of explicit MPC.

Explicit Model Predictive Control for Inverted Pendulum Systems

Model Predictive Control is a control technique that has been greatly investigated in recent years. It has the versatility of different types of models for the prediction of the system and aptitude to handle the system constraints. In the last decade, the multi-parametric optimization has been applied to the control theory that allowed for the MPC optimization to be performed offline, which was denominated as explicit Model Predictive Control. This work investigates the application of this control technique in Inverted Pendulum systems, which are commonly used as didactic control systems. The complete control design is described considering its validation for two Inverted Pendulum systems through simulations.