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An Iterative Optimization Approach for Fuzzy Predictive Control

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Abstract

This paper proposes an iterative approach in fuzzy model predictive control. When the prediction model is nonlinear or uncertain, non-convex optimization is often encountered which has to be solved by iterative approximation. An alternative is to convert the original issue into a min-max robust MPC problem, where the knowledge of the predictive membership function is not utilized. In this paper, based on the robust MPC approach, we further enhance the model prediction by iteratively applying the optimal control move and state sequences in order to improve the performance. A numerical example is provided to illustrate the effectiveness of the proposed approach.

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Authors and Affiliations

  1. School of Optoelectronics and Engineering, Xi’an Technological University, Xi’an, China

    Yuanqing Yang

  2. College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Baocang Ding

Authors
  1. Yuanqing Yang
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  2. Baocang Ding
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Correspondence to Baocang Ding.

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Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Jiuxiang Dong under the direction of Editor Euntai Kim. This work is supported by NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (No. U1809207).

Yuangqing Yang received his M.S. degree from Northwestern Polytechnical University, and his Ph.D. degree from Xi'an Jiao-tong University. His research interest include model predictive control, network control, and distributed control systems.

Baocang Ding was born in Hebei Province, China. He received his M.S. degree from the China University of Petroleum, Beijing, China, in 2000 and a Ph.D. degree from Shanghai Jiaotong University, Shanghai, China, in 2003. From September 2005 to September 2006, he was a Postdoctoral Research Fellow in Department of Chemical and Materials Engineering, University of Alberta, Canada. From November 2006 to August 2007, he was a Research Fellow in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Dr. Ding was the recipient of the 2009 Program for New Century Excellent Talents in University of China. He is currently a full Professor with Chongqing University of Posts and Telecommunications. His research interests include predictive control, fuzzy control, networked control, and distributed control systems.

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Yang, Y., Ding, B. An Iterative Optimization Approach for Fuzzy Predictive Control. Int. J. Control Autom. Syst. 18, 2157–2164 (2020). https://doi.org/10.1007/s12555-019-0488-4

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  • DOI: https://doi.org/10.1007/s12555-019-0488-4

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