Model-Free Predictive Control and Its Applications

Muhammad Nauman, Wajiha Shireen and Amir Hussain
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Muhammad Nauman: Departemnt of Electrical and Computer Engineering, The University of Houston, Houston, TX 77204, USA
Wajiha Shireen: Department of Electrical Technology, The University of Houston, Houston, TX 77204, USA
Amir Hussain: Texas Instruments, Sugar Land, TX 77479, USA

Energies, 2022, vol. 15, issue 14, 1-24

Abstract: Predictive control offers many advantages such as simple design and a systematic way to handle constraints. Model predictive control (MPC) belongs to predictive control, which uses a model of the system for predictions used in predictive control. A major drawback of MPC is the dependence of its performance on the model of the system. Any discrepancy between the system model and actual plant behavior will greatly affect the performance of the MPC. Recently, model-free approaches have been gaining attention because they are not dependent on the system model parameters. To obtain the advantages of both a model-free approach and predictive control, model-free predictive control (MFPC) is being explored and reported in the literature for different applications such as power electronics and electric drives. This paper presents an overview of model-free predictive control. A comprehensive review of the application of MFPC in power converters, electric drives, power systems, and microgrids is presented in this paper. Moreover, challenges, opportunities, and emerging trends in MFPC are also discussed in this paper.

Keywords: model-free control; model predictive control; model-free predictive control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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