The optimal control of semi-active suspension based on improved particle swarm optimization

Q4 Engineering
Haijing Yan, Jubin Qiao, Sen Zhang, Ting Zhao, Zhongchang Wang
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引用次数: 3

Abstract

For the lack of artificial experience in weighted matrix Q and R in LQR optimal control algorithm of suspension, this paper proposed an optimal control strategy based on improved particle swarm optimization for semi-active suspension system. The paper mainly established a quarter vehicle semi-active suspension system model in MatLab, and wrote the S-function of the optimal controller. In addition, this article optimized weighted coefficient matrix Q of the state variable and the weighted coefficient matrix R of the control variable in the linear quadratic regulator (LQR) [1] by utilizing the improved particle swarm optimization. The simulation results showed that the semi-active suspension system which based on the improved particle swarm optimization (IPSO) had better ride comfort and smoothness.
基于改进粒子群优化的半主动悬架优化控制
针对悬架LQR最优控制算法中加权矩阵Q和R的人工经验不足,提出了一种基于改进粒子群优化的半主动悬架系统最优控制策略。本文主要在MatLab中建立了四分之一车辆半主动悬架系统模型,并编写了最优控制器的S函数。此外,本文利用改进的粒子群优化方法对线性二次型调节器[1]中状态变量的加权系数矩阵Q和控制变量的加权系数组R进行了优化。仿真结果表明,基于改进粒子群优化算法的半主动悬架系统具有较好的平顺性和平顺性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.10
自引率
0.00%
发文量
8
审稿时长
10 weeks
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