李维波, 张浩, 徐成虎, 等. 基于蜘蛛蜂算法的EHA滑模控制器优化研究[J]. 中国舰船研究, 2024, 19(X): 1–8. DOI: 10.19693/j.issn.1673-3185.03815
引用本文: 李维波, 张浩, 徐成虎, 等. 基于蜘蛛蜂算法的EHA滑模控制器优化研究[J]. 中国舰船研究, 2024, 19(X): 1–8. DOI: 10.19693/j.issn.1673-3185.03815
shu
LI W B, ZHANG H, XU C H, et al. Optimization of EHA sliding mode controller based on spider wasp algorithm[J]. Chinese Journal of Ship Research, 2024, 19(X): 1–8 (in Chinese). DOI: 10.19693/j.issn.1673-3185.03815
Citation: LI W B, ZHANG H, XU C H, et al. Optimization of EHA sliding mode controller based on spider wasp algorithm[J]. Chinese Journal of Ship Research, 2024, 19(X): 1–8 (in Chinese). DOI: 10.19693/j.issn.1673-3185.03815
shu

基于蜘蛛蜂算法的EHA滑模控制器优化研究

Optimization of EHA sliding mode controller based on spider wasp algorithm

    摘要
  • 摘要:
    目的 为实现电动静液作动器（EHA）的精确位置控制并降低滑模控制器的参数整定难度，提高滑模控制器的综合性能，提出采用蜘蛛蜂优化算法（SWO）对控制器参数进行整定。
    方法 建立电动静液作动器的简化模型，设计相应的滑模控制器，并利用SWO算法对该控制器的滑模面和趋近率参数进行整定，进而使用Matlab/Simulink和AMEsim仿真软件搭建联合仿真模型进行验证。
    结果 通过手动方式和SWO算法分别整定滑模控制器参数，其对比仿真结果表明：SWO算法优化后的滑模控制器避免了超调，提高了抗干扰性，且收敛速度提高了33.6%，证明了采用蜘蛛蜂算法优化EHA滑模控制器的滑模面和趋近率参数的可行性。
    结论 研究成果可为EHA滑模控制器设计提供理论参考。

     

    Abstract:
    Objectives This paper proposes using a spider wasp optimization (SWO) algorithm to realize the 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.
    Conclusions The results of this study can provide theoretical references for the design of EHA sliding mode controllers.

     

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