A review of finite control set model predictive control for linear machines

Abstract

Abstract Linear machines (LMs) have become excellent candidates for linear motion applications due to their abilities of generating thrust without any transmissions, and have been widely adopted in transportation, industries etc. Among the numerous control methods of LM drive systems, finite control set model predictive control (FCS‐MPC) method has been given special attention due to its clear concept, fast response performance, and ability to handle constrained multivariate non‐linear control problems. It is widely used to improve the performance and efficiency of overall LM drive systems. Firstly, based on the three elements of FCS‐MPC, the advantages and shortcomings of the FCS‐MPC method in applications are fully investigated. The research status in FCS‐MPC has been summarised, such as multistep MPC, parameters robustness improvement, fast optimisation, and multi‐vector MPC. Then, the key issues in FCS‐MPC such as delay compensation, parameters design, and stability analysis are discussed, and their typical research methods and current research status are explained. Finally, the future development trends of FCS‐MPC in LM drive systems are discussed.

Keywords

• fast optimization
• finite control set model predictive control
• linear machines
• multi‐vector model predictive control
• parameters robustness