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Article type: Research Article
Authors: Xiao, Yanjuna; b; * | Zhao, Churuia; b | Qi, Haoa | Liu, Weilinga | Meng, Zhaozonga | Peng, Kaia; 1
Affiliations: [a] School of Mechanical Engineering, Tianjin Key Laboratory of Power Transmission and Safety Technology for NewEnergy Vehicles, Hebei University of Technology, Tianjin, China | [b] Career Leader intelligent control automation company, Suqian, Jiangsu Province, China
Correspondence: [*] Corresponding author. Yanjun Xiao, E-mail: [email protected].
Note: [1] This paper is a project supported by the natural science foundation of Hebei Province, China, which studies the theory and method of intelligent scheduling of textile production line based on cloud edge end collaboration.
Abstract: In the control system of a lithium battery rolling mill, the correction system was crucial. This was because the correction system had a significant impact on the performance of the lithium battery rolling mill, including high precision and efficient rolling quality. However, the non-linearity of the correction system and the uncertainty of the correction system made it a challenging problem to achieve a high precision correction control. The contribution and innovation of this paper was a genetic fuzzy PID control strategy based on Kalman filter, which was proposed and applied to the control of lithium battery rolling mill correction technology. In order to achieve intelligent control of a high-precision electrode rolling mill correction system, an algorithm fusion control scheme was proposed. Firstly, a novel and detailed correction system model was presented. Next, the initial PID parameters of the correction were optimized by means of a genetic algorithm so that the PID parameters could be adapted to the correction control process and then optimized again by adding an extended Kalman filter. Finally, the lithium battery rolling mill correction control system was validated, tested and commissioned in the field. The results showed that the designed algorithm could meet the working requirements of the lithium battery rolling mill and that it improved the accuracy of the correction system. In the actual lithium battery rolling mill production process, the algorithm was compared with a conventional PID. Compared with the common single algorithm, the fusion algorithm proposed in this paper was a complete set of high precision correction control system algorithm to solve the high precision problem faced by the correction system in the actual lithium battery rolling mill correction system.
Keywords: Pole piece rolling mill, deviation correction system, fuzzy PID, genetic algorithm, algorithm fusion, extended kalman filter
DOI: 10.3233/JIFS-221028
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 2, pp. 2503-2523, 2023
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