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Liquid Level Tracking Control of Three-tank Systems

Abstract

In this paper, a liquid level tracking controller composed of a feedforward controller and a feedback controller is proposed for three-tank systems. Firstly, the flat property of three-tank systems is verified and a feedforward controller is designed accordingly to track the ideal trajectories. Secondly, in order to eliminate the tracking errors introduced by model uncertainties or unknown disturbances, a nonlinear model predictive controller is designed in which a terminal equality constraint is added for ensuring asymptotic convergence. In addition, an improved cuckoo search algorithm is adopted to solve the optimization problem involved in the nonlinear model predictive control. Finally, the control performance is confirmed by both simulation and experiment results.

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Affiliations

Authors

Corresponding author

Correspondence to Shuyou Yu.

Additional information

Recommended by Associate Editor Niket Kaisare under the direction of Editor Jay H. Lee.

This work was supported by the National Natural Science Foundation of China (No. U1964202, No. 61711540307, No. 61703176, No. 61703178, No. 61520106008).

Shuyou Yu received his B.S. and M.S. degrees in control science and engineering from Jilin University, China, in 1997 and 2005, respectively, and a Ph.D. degree in engineering cybernetics from the University of Stuttgart, Germany, in 2011. From 2010 to 2011, he was a Research and Teaching Assistant with the Institute for Systems Theory and Automatic Control, University of Stuttgart. In 2012, he joined the Department of Control Science and Engineering, Jilin University, as a Faculty Member, where he is currently a Full Professor. His main research interests include model predictive control, robust control, and its applications in mechatronic systems.

Xinghao Lu received his B.E. degree from the College of Communication Engineering, Jilin University, in 2019. He is currently pursuing a master’s degree with the Department of Control Science and Engineering, Jilin University. His research interests include model predictive control and machine learning.

Yu Zhou received her B.E. degree from the Jilin Jianzhu University, China, in 2016, and an M.S. degree in control science and engineering from Jilin University, China, in 2019. During the master’s degree, she mainly studied nonlinear control strategies of three-tank systems.

Yangyang Feng received his B.E. degree from the Jilin Agricultural University, China, in 2016, and an M.S. degree in the control science and engineering from Jilin University, China, in 2019. He is currently pursuing a Ph.D. degree with the Department of Control Science and Engineering, Jilin University, China. His research interests include nonlinear control, adaptive control, and system identification.

Ting Qu received her B.S. and M.S. degrees from the Northeast Normal University, Changchun, China, in 2006 and 2008, respectively, and a Ph.D. in control science and engineering from the Jilin University of China in 2015. Since 2015, she is a lecturer with the State Key Laboratory of Automotive Simulation and Control at the Jilin University, China. Her research interests include model predictive control and driver modeling.

Hong Chen received her B.S. and M.S. degrees in process control from Zhejiang University, Zhejiang, China, in 1983 and 1986, respectively, and a Ph.D. degree in system dynamics and control engineering from the University of Stuttgart, Stuttgart, Germany, in 1997. Since 1999, she has been a professor at Jilin University, Changchun, China, where she currently serves as Tang Aoqing Professor and as the director of the State Key Laboratory of Automotive Simulation and Control. Her current research interests include model predictive control, optimal and robust control, nonlinear control and applications in mechatronic systems focusing on automotive systems.

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Cite this article

Yu, S., Lu, X., Zhou, Y. et al. Liquid Level Tracking Control of Three-tank Systems. Int. J. Control Autom. Syst. 18, 2630–2640 (2020). https://doi.org/10.1007/s12555-018-0895-y

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Keywords

  • Cuckoo search algorithm
  • flat system
  • liquid level tracking
  • model predictive control