Model-Free Predictive Control of Motor Drives: A Review

Abstract

Model predictive control (MPC) has been deemed as an attractive control method in motor drives by virtue of its simple structure, convenient multi-objective optimization, and satisfactory dynamic performance. However, the strong reliance on mathematical models seriously restrains its practical application. Therefore, improving the robustness of MPC has attained significant attentions in the last two decades, followed by which, model-free predictive control (MFPC) comes into existence. This article aims to reveal the current state of MFPC strategies for motor drives and give the categorization from the perspective of implementation. Based on this review, the principles of the reported MFPC strategies are introduced in detail, as well as the challenges encountered in technology realization. In addition, some of typical and important concepts are experimentally validated via case studies to evaluate the performance and highlight their features. Finally, the future trends of MFPC are discussed based on the current state and reported developments.