Parameter tuning of auto disturbance rejection controller based on improved glowworm swarm optimization algorithm
ISSN: 0144-5154
Article publication date: 25 May 2022
Issue publication date: 19 July 2022
Abstract
Purpose
This paper aims to study a parameter tuning method for the active disturbance rejection control (ADRC) to improve the anti-interference ability and position tracking of the performance of the servo system, and to ensure the stability and accuracy of practical applications.
Design/methodology/approach
This study proposes a parameter self-tuning method for ADRC based on an improved glowworm swarm optimization algorithm. The algorithm is improved by using sine and cosine local optimization operators and an adaptive mutation strategy. The improved algorithm is then used for parameter tuning of the ADRC to improve the anti-interference ability of the control system and ensure the accuracy of the controller parameters.
Findings
The authors designed an optimization model based on MATLAB, selected examples of simulation and experimental research and compared it with the standard glowworm swarm optimization algorithm, particle swarm algorithm and artificial bee colony algorithm. The results show that the response time of using the improved glowworm swarm optimization algorithm to optimize the auto-disturbance rejection control is short; there is no overshoot; the tracking process is relatively stable; the anti-interference ability is strong; and the optimization effect is better.
Originality/value
The innovation of this study is to improve the glowworm swarm optimization algorithm, propose a sine and cosine, local optimization operator, expand the firefly search space and introduce a new adaptive mutation strategy to adaptively adjust the mutation probability based on the fitness value, improve the global search ability of the algorithm and use the improved algorithm to adjust the parameters of the active disturbance rejection controller.
Keywords
Acknowledgements
Declaration of conflicting interests: The author(s) declared no potential conflict of interests concerning the research, authorship and/or publication of this paper.
Funding: This work was supported by the Natural Science Foundation of Heilongjiang Province of China (LH2019E064), and National Natural Science Foundation of China (52075134).
Citation
Gao, B., Shen, W., Dai, Y. and Ye, Y.T. (2022), "Parameter tuning of auto disturbance rejection controller based on improved glowworm swarm optimization algorithm", Assembly Automation, Vol. 42 No. 4, pp. 427-444. https://doi.org/10.1108/AA-12-2021-0188
Publisher
:Emerald Publishing Limited
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