基于路面等级自适应的主动悬架LQG控制

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振动与冲击 ›› 2020, Vol. 39 ›› Issue (23) : 30-37.

论文

基于路面等级自适应的主动悬架LQG控制

寇发荣，高亚威，景强强，彭先龙，王星

作者信息 +

LQG control of active suspension based on adaptive road surface level

KOU Farong, GAO Yawei, JING Qiangqiang, PENG Xianlong, WANG Xing

Author information +

文章历史 +

摘要

为了解决车辆在混合等级路面时平顺性与操纵稳定性差的问题，提出了一种基于路面等级自适应的主动悬架LQG控制策略。根据路面功率谱密度与国际平整度指数的关系识别路面等级；以不同路面等级为阈值，确定三种控制目标；计算每次迭代后平均味道浓度判定值的方差确定迭代步长，解决了果蝇算法过早收敛和迭代次数过长的问题；在不同控制目标下设立了相应的适应度函数，并利用改进后的果蝇算法优化不同适应度函数下LQG控制的加权系数，以此提高混合等级路面下的控制性能。仿真分析了在不同等级路面下的悬架动态性能，并进行了道路实车试验。仿真结果表明，相比传统LQG控制，基于路面等级自适应LQG控制的悬架系统在A级路面下簧载质量加速度均方根值减小16.34%，在D路面下轮胎动载荷均方根值减小6.51%，在B级和C级路面下，簧载质量加速度和轮胎动载荷的均方根值分别减小9.59%、7.54%和11.32%、9.4%；试验结果与仿真结果基本一致。

Abstract

In order to solve the problem of poor ride comfort and handling stability of vehicles on mixed level road surfaces, a LQG control strategy of active suspension based on adaptive road surface level was proposed.The road surface level was identified according to the relationship between pavement power spectral density and international roughness index.Three kinds of control objectives were determined with different road surface levels taken as thresholds, and the variance of judgment value of average taste concentration after each iteration was calculated to determine next iteration step length to solve problems of premature convergence and long iteration times of Drosophila algorithm.The corresponding fitness functions were set up under different control objectives, and the improved Drosophila algorithm was used to optimize the weighting coefficient of LQG control under different fitness functions to improve the control performance under mixed level road surface.The dynamic performance of the suspension under different levels of road surface was simulated and analyzed, and real vehicle tests were conducted on road.The simulation results showed that compared with the traditional LQG control, the proposed suspension system based on pavement level adaptive LQG control can reduce the RMS value of the spring loaded mass acceleration by 16.34% under A-level road surface, and the RMS value of the tire dynamic load by 6.51% under D-road surface; RMS values of spring loaded mass acceleration and tire dynamic load can be reduced by 9.59% and 7.54% under B-road surface, and 11.32% and 9.4% under C-road surface, respectively; test results are basically consistent to simulation ones.

导出引用

寇发荣，高亚威，景强强，彭先龙，王星. 基于路面等级自适应的主动悬架LQG控制[J]. 振动与冲击, 2020, 39(23): 30-37

KOU Farong, GAO Yawei, JING Qiangqiang, PENG Xianlong, WANG Xing. LQG control of active suspension based on adaptive road surface level[J]. Journal of Vibration and Shock, 2020, 39(23): 30-37

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