基于改进粒子群算法的精密隔振系统LQR控制
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中北大学机械工程学院 太原 030051

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TP273;TB535.1

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山西省面上自然科学基金项目(201801D121184)资助


LQR control of precision vibration isolation system based on an improved particle swarm algorithm
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School of Mechanical Engineering NCU, North University of China, Taiyuan 030051, China

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    摘要:

    为解决线性二次型控制器(LQR)权值参数难以通过经验选取最优组合的问题,采用一种贪婪Lévy PSO算法对LQR权值矩阵Q进行寻优。传统粒子群算法易局部收敛,在此基础上加入Lévy飞行原理和贪婪选择方法从而扩大参数寻优范围且提高收敛速度,得出最优权值矩阵Q。对在LQR控制下的双层精密隔振系统模型在扫频激励和随机激励两种情况时隔振对象的加速度响应和位移响应进行分析。最终结果为收敛速度提升75%,针对两种激励情况的加速和位移削弱程度均在90%以上。仿真结果表明贪婪Lévy PSO算法可有效增加种群分布的均匀性提高收敛速度寻得最优解,且在更短的时间内寻得更好的结果,两种激励情况时均能有效实现隔振。

    Abstract:

    In order to solve the problem that it is difficult to select the optimal combination of linear quadratic controller (LQR) weight parameters through experience, a Lévy flying particle swarm algorithm with greedy principle is proposed to optimize the LQR weight matrix Q. The traditional particle swarm algorithm is easy to locally converge. On this basis, the Lévy flight principle and the greedy selection method are added to expand the parameter optimization range and increase the convergence speed, and the optimal weight matrix Q is obtained. The acceleration response and displacement response of the vibration isolation object under the two-layer precision vibration isolation system model under the control of LQR are analyzed under the conditions of sweep frequency excitation and random excitation. The simulation results show that the Lévy flying particle swarm algorithm with the principle of greed is effective Increasing the uniformity of the population distribution improves the convergence speed to find the optimal solution, and can effectively achieve vibration isolation in both excitation conditions.

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范 伟,孟 江,杜永飞,蒋 童,刘 凯.基于改进粒子群算法的精密隔振系统LQR控制[J].电子测量技术,2022,45(2):104-109

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  • 在线发布日期: 2024-06-17
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