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Publishing Language: Chinese

Optimization of EHA sliding mode controller based on spider wasp algorithm

Weibo LI1,2( ), Hao ZHANG1, Chenghu XU1, Maojie ZHANG1, Hualiang FANG3
School of Automation, Wuhan University of Technology, Wuhan 430070, China
College of Electrical Engineering, Northwest Minzu University, Lanzhou 730124, China
School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
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Abstract

Objective

This paper proposes using the Spider Wasp Optimization (SWO) algorithm to achieve precise position control of an electro-hydrostatic actuator (EHA) while reducing the parameter tuning difficulty of the EHA sliding mode controller and improving its comprehensive performance.

Methods

A simplified model of an EHA is established and its sliding mode controller is designed. The sliding mode surface and reaching rate parameters of the controller are then adjusted by the SWO algorithm, and Matlab/Simulink and AMEsim simulation software is used to build a co-simulation model for verification.

Results

The parameters of the sliding mode controller are adjusted manually and by the SWO algorithm respectively. The comparative simulation results show that the sliding mode controller optimized by the SWO algorithm avoids overshoot and has enhanced anti-interference properties, and its convergence speed is improved by 33.6%, proving the feasibility of optimizing the sliding surface and reaching rate parameters of an EHA sliding mode controller using the SWO algorithm.

Conclusion

The results of this study can provide theoretical references for the design of EHA sliding mode controllers.

Keywords

EHA equipmentsliding-mode controloptimizationspider wasp optimizerjoint simulation
CLC number: U665.13 Document code: A

References

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Chinese Journal of Ship Research
Volume 20 Issue 4,
August 2025
Pages 246-253
DOI: 10.19693/j.issn.1673-3185.03815

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Cite this article:
LI W, ZHANG H, XU C, et al. Optimization of EHA sliding mode controller based on spider wasp algorithm. Chinese Journal of Ship Research, 2025, 20(4): 246-253. https://doi.org/10.19693/j.issn.1673-3185.03815

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Received: 08 March 2024
Revised: 12 April 2024
Published: 15 July 2024
© 2025 Chinese Journal of Ship Research.