Optimized control strategy based on EPCH and DBMP algorithms for quadruple-tank liquid level system

Authors

Xiangxiang Meng, Haisheng Yu, Jie Zhang, Kejia Yan

Abstract

According to the actual production requirements in process control, this paper proposes an optimized control strategy for the quadruple-tank liquid level system (QTLLS). Firstly, using the Bernoulli’s law and mass conservation principle, the dynamic mathematical model of QTLLS is established and linearized. Secondly, the state error port controlled Hamiltonian (EPCH) controller is designed by Hamiltonian system model construction which utilize the Hamiltonian principle, and a disturbance observer(DOB) is chosen to compensate disturbances impact. Thirdly, a deadbeat model predictive (DBMP) control algorithm with discrete-time disturbance observer (DTDOB) is proposed. Finally, in order to establish an optimized control strategy, an optimized function is proposed, which can give full play to the advantages of DBMP-OB algorithm with fast dynamic response and EPCH-OB algorithm with good steady-state performance. A wealth of results from simulation and experimental fully confirm the superiority of the proposed control strategies compare with proportional–integral–derivative (PID) control and sliding mode control (SMC). Moreover, the proposed optimized control strategy has been realized position control, tracking control and disturbance compensation control in this paper. It meets the needs of production and has great industrial application prospects.

Keywords

dbmp control, optimized function, qtlls, state epch control

Citation

• Journal: Journal of Process Control
• Year: 2022
• Volume: 110
• Issue:
• Pages: 121–132
• Publisher: Elsevier BV
• DOI: 10.1016/j.jprocont.2021.12.008

BibTeX

@article{Meng_2022,
  title={{Optimized control strategy based on EPCH and DBMP algorithms for quadruple-tank liquid level system}},
  volume={110},
  ISSN={0959-1524},
  DOI={10.1016/j.jprocont.2021.12.008},
  journal={Journal of Process Control},
  publisher={Elsevier BV},
  author={Meng, Xiangxiang and Yu, Haisheng and Zhang, Jie and Yan, Kejia},
  year={2022},
  pages={121--132}
}

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