research-article

Temperature Control of Continuous Stirred Tank Reactor Based on RTO-ANN-MPC

Authors: Yihang Liu, Bing XuAuthors Info & Claims

ICCIR '24: Proceedings of the 2024 4th International Conference on Control and Intelligent Robotics

Pages 234 - 238

Published: 18 November 2024 Publication History

Abstract

To solve the problems of nonlinearity, complex reaction mechanism, high energy consumption, etc. of continuous stirred tank reactor (CSTR) in chemical production, this paper combines real-time optimization (RTO) with artificial neural network (ANN) and model predictive control (MPC). The occurrence of endothermic reaction in the reactor is simulated based on the theory of chemical reaction kinetics. The combination of RTO and MPC plays a good role in balancing energy costs and improving control effects. ANN's ability to approximate unknown nonlinear functions solves the problem that RTO and MPC can only be applied to linear models. The results show that this method has a good control effect on temperature.

References

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Zhang L, Xie L, Su H, et al. Data-driven auto-tuning strategy for RTO-MPC based on Bayesian optimization[J]. Computers & Chemical Engineering, 2024: 108743.

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Santana D D, Martins M A F, Odloak D. One-layer gradient-based MPC+ RTO strategy for unstable processes: a case study of a CSTR system[J]. Brazilian Journal of Chemical Engineering, 2020, 37(1): 173-188.

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Index Terms

Temperature Control of Continuous Stirred Tank Reactor Based on RTO-ANN-MPC
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis

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ICCIR '24: Proceedings of the 2024 4th International Conference on Control and Intelligent Robotics

June 2024

399 pages

ISBN:9798400709937

DOI:10.1145/3687488

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Association for Computing Machinery

New York, NY, United States

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Published: 18 November 2024

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ICCIR 2024

ICCIR 2024: 2024 4th International Conference on Control and Intelligent Robotics

June 21 - 23, 2024

Guangzhou, China

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Overall Acceptance Rate 131 of 239 submissions, 55%

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Abstract

References

Index Terms

Recommendations

Neural network control for a class of continuous stirred tank reactor process with dead-zone input

Brief Continuous stirred tank reactors: easy to stabilise?

Application of generalized predictive control in temperature control of continuous stirred tank reactor

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