Abstract

Predictive control has emerged as a promising control method in a variety of technological fields. Model predictive control, as one of the subdivisions of this control method, has found a growing number of applications in power electronics and motor drives. In practical implementations, model predictive control faces performance degradation of the controlled plant due to its dependency on a model. There are considerable numbers of review papers that are devoted to the different points of view of predictive control. However, the existing literature lacks a review study that addresses the solutions for parameter dependency of the model predictive control method. Recently, model-free predictive control has been used in drives and power electronics as a solution for dealing with the model-dependency of the model predictive control method. There are many papers that have used such methods. In this paper, a classification is proposed for the different implementation types of model-free predictive control or similar methods that address model parameter uncertainties. Additionally, a comparison between the methods is also presented.

Highlights

  • Predictive control has been considered as a part of optimal control theory since 1960s [1]

  • The early approach of robust model predictive control (MPC) is based on min–max optimal control problem formulations in which the controller acts according to the worst-case evaluations of the cost function

  • Another review surveys the three decades of development of the model predictive control; this paper divides the growth of the method into three steps, each belonging to one decade [8]

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Summary

INTRODUCTION

Predictive control has been considered as a part of optimal control theory since 1960s [1]. In [15], a survey on predictive control methods in power electronics and drive systems is presented with an informative classification It emphasizes that the control system’s performance generally depends on the accuracy of the plant model. This paper first presents the basic formulation and structure of major MFPC strategies according to a novel comprehensive classification and addresses various methods of MFPC as applied to motor drives and power electronic converters. It elaborates on the basic analytical and implementation aspects of the control methods by introducing a novel classification.

LITERATURE REVIEW
Principles of Model-Free Predictive Control
Findings
Conclusion
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