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Dynamic output feedback robust MPC for LPV systems subject to input saturation and bounded disturbance

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  • Control Theory and Applications
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Abstract

For linear parameter varying (LPV) systems with unknown scheduling parameters and bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC) with input saturation is investigated. By pre-specifying partial controller parameters, a main optimization problem is solved by convex optimization to reduce the on-line computational burden. The main optimization problem guarantees that the estimated state and estimation error converge within the corresponding invariant sets such that recursive feasibility and robust stability are guaranteed. The consideration of input saturation in the main optimization problem improves the control performance. Two numerical examples are given to illustrate the effectiveness of the approach.

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Author information

Authors and Affiliations

  1. School of Electro-Mechanical Engineering, Xidian University, Xi’an, 710071, China

    Xubin Ping & Zhiwu Li

  2. Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau

    Zhiwu Li

  3. FARCAMT, Advanced Manufacturing Institute, King Saud University, Riyadh, 11421, Saudi Arabia

    Abdulrahman Al-Ahmari

  4. Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia

    Abdulrahman Al-Ahmari

Authors
  1. Xubin Ping
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  2. Zhiwu Li
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  3. Abdulrahman Al-Ahmari
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Corresponding author

Correspondence to Xubin Ping.

Additional information

Recommended by Associate Editor Sukho Park under the direction of Editor PooGyeon Park. This work was funded by the National Nature Science Foundation of China (NSFC, 61403297). The authors extend their appreciation to the International Scientific Partnership Program ISPP at King Saud University for funding this research Work through ISPP#0079

Xubin Ping received the Bachelor’s degree from Northwest University, Xi’an, China, in 2005 and the Master’s degree from the East China University of Science and Technology, Shanghai, China, in 2008 and the Ph.D. degree from Xi’an Jiaotong University, Xi’an, China, in 2013. His research interests include robust control, model predictive control.

Zhiwu Li received the B.S., M.S., and Ph.D. degrees in mechanical engineering, automatic control, and manufacturing engineering, respectively, all from Xidian University, Xi’an, China, in 1989, 1992, and 1995, respectively. He joined Xidian University in 1992 and now he is also with the Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau. Over the past decade, he was a Visiting Professor at the University of Toronto, Technion-Israel Institute of Technology, Martin-Luther University of Halle-Wittenburg, Conservatoire National des Arts et Métiers (CNAM), Meliksah Universitesi. His current research interests include Petri net theory and application, supervisory control of discrete event systems, workflow modeling and analysis, system reconfiguration, game theory, and data and process mining.

He is a member of Discrete Event Systems Technical Committee of the IEEE Systems, Man, and Cybernetics Society, and a member of IFAC Technical Committee on Discrete Event and Hybrid Systems from 2011 to 2014. He serves as a frequent reviewer for 40+ international journals including Automatica and a number of the IEEE Transactions as well as many international conferences. He is listed in Marquis Who’s Who in the world, 27th Edition, 2010. Dr. Li is a recipient of an Alexander von Humboldt Research Grant, Alexander von Humboldt Foundation, Germany. He is a Fellow of IEEE and is the founding chair of Xi’an Chapter of IEEE Systems, Man, and Cybernetics Society.

Abdulrahman Al-Ahmari received his Ph.D. in Manufacturing Systems Engineering from the University of Sheffield in 1998. He was selected as a gust editor for several special issues of induration journals such as International Journal of Collaborative Enterprise, and International Journal of Rapid Manufacturing. His research interests are in advanced manufacturing technologies, additive manufacturing and 3D printing, Petri nets, analysis and design of manufacturing systems, Computer Integrated Manufacturing (CIM), optimization of manufacturing operations, FMS and cellular manufacturing systems and applications of DSS in manufacturing.

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Ping, X., Li, Z. & Al-Ahmari, A. Dynamic output feedback robust MPC for LPV systems subject to input saturation and bounded disturbance. Int. J. Control Autom. Syst. 15, 976–985 (2017). https://doi.org/10.1007/s12555-016-0004-z

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  • DOI: https://doi.org/10.1007/s12555-016-0004-z

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