Proportion integral-type active disturbance rejection generalized predictive control for distillation process based on grey wolf optimization parameter tuning

doi:10.1016/j.cjche.2021.11.022

中国化学工程学报 ›› 2022, Vol. 49 ›› Issue (9): 234-244.DOI: 10.1016/j.cjche.2021.11.022

Proportion integral-type active disturbance rejection generalized predictive control for distillation process based on grey wolf optimization parameter tuning

Jia Ren¹, Zengqiang Chen^1,2, Mingwei Sun¹, Qinglin Sun¹, Zenghui Wang³

1. College of Artificial Intelligence, Nankai University, Tianjin 300350, China;
2. Key Lab of Intelligent Robotics of Tianjin, Tianjin 300350, China;
3. Department of Electrical and Mining Engineering, University of South Africa, Florida 1710, South Africa

收稿日期:2021-07-29 修回日期:2021-11-25 发布日期:2022-10-19
通讯作者: Zengqiang Chen,E-mail:chenzq@nankai.edu.cn
基金资助:
This work was funded by the National Natural Science Foundation of China (61973175, 62073177 and 61973172), South African National Research Foundation (132797), South African National Research Foundation Incentive (114911), Eskom Tertiary Education Support Programme Grant of South Africa, and Tianjin Research Innovation Project for Postgraduate Students (2021YJSB018, 2020YJSB003).

Proportion integral-type active disturbance rejection generalized predictive control for distillation process based on grey wolf optimization parameter tuning

Jia Ren¹, Zengqiang Chen^1,2, Mingwei Sun¹, Qinglin Sun¹, Zenghui Wang³

1. College of Artificial Intelligence, Nankai University, Tianjin 300350, China;
2. Key Lab of Intelligent Robotics of Tianjin, Tianjin 300350, China;
3. Department of Electrical and Mining Engineering, University of South Africa, Florida 1710, South Africa

Received:2021-07-29 Revised:2021-11-25 Published:2022-10-19
Contact: Zengqiang Chen,E-mail:chenzq@nankai.edu.cn
Supported by:
This work was funded by the National Natural Science Foundation of China (61973175, 62073177 and 61973172), South African National Research Foundation (132797), South African National Research Foundation Incentive (114911), Eskom Tertiary Education Support Programme Grant of South Africa, and Tianjin Research Innovation Project for Postgraduate Students (2021YJSB018, 2020YJSB003).

摘要/Abstract

摘要： The high-purity distillation column system is strongly nonlinear and coupled, which makes it difficult to control. Active disturbance rejection control (ADRC) has been widely used in distillation systems, but it has limitations in controlling distillation systems with large time delays since ADRC employs ESO and feedback control law to estimate the total disturbance of the system without considering the large time delays. This paper designs a proportion integral-type active disturbance rejection generalized predictive control (PI-ADRGPC) algorithm to control the distillation column system with large time delay. It replaces the PD controller in ADRC with a proportion integral-type generalized predictive control (PI-GPC), thereby improving the performance of control systems with large time delays. Since the proposed controller has many parameters and is difficult to tune, this paper proposes to use the grey wolf optimization (GWO) to tune these parameters, whose structure can also be used by other intelligent optimization algorithms. The performance of GWO tuned PI-ADRGPC is compared with the control performance of GWO tuned ADRC method, multi-verse optimizer (MVO) tuned PI-ADRGPC and MVO tuned ADRC. The simulation results show that the proposed strategy can track reference well and has a good disturbance rejection performance.

关键词: Proportion integral-type active disturbance rejection generalized predictive control, Grey wolf optimization, Parameter tuning, Distillation, Process control, Prediction

Abstract: The high-purity distillation column system is strongly nonlinear and coupled, which makes it difficult to control. Active disturbance rejection control (ADRC) has been widely used in distillation systems, but it has limitations in controlling distillation systems with large time delays since ADRC employs ESO and feedback control law to estimate the total disturbance of the system without considering the large time delays. This paper designs a proportion integral-type active disturbance rejection generalized predictive control (PI-ADRGPC) algorithm to control the distillation column system with large time delay. It replaces the PD controller in ADRC with a proportion integral-type generalized predictive control (PI-GPC), thereby improving the performance of control systems with large time delays. Since the proposed controller has many parameters and is difficult to tune, this paper proposes to use the grey wolf optimization (GWO) to tune these parameters, whose structure can also be used by other intelligent optimization algorithms. The performance of GWO tuned PI-ADRGPC is compared with the control performance of GWO tuned ADRC method, multi-verse optimizer (MVO) tuned PI-ADRGPC and MVO tuned ADRC. The simulation results show that the proposed strategy can track reference well and has a good disturbance rejection performance.

Key words: Proportion integral-type active disturbance rejection generalized predictive control, Grey wolf optimization, Parameter tuning, Distillation, Process control, Prediction

Jia Ren, Zengqiang Chen, Mingwei Sun, Qinglin Sun, Zenghui Wang. Proportion integral-type active disturbance rejection generalized predictive control for distillation process based on grey wolf optimization parameter tuning[J]. 中国化学工程学报, 2022, 49(9): 234-244.

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Proportion integral-type active disturbance rejection generalized predictive control for distillation process based on grey wolf optimization parameter tuning

Proportion integral-type active disturbance rejection generalized predictive control for distillation process based on grey wolf optimization parameter tuning

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