基于改进遗传算法的半主动悬架系统模糊控制优化研究  

RESEARCH ON THE FUZZY CONTROL OF SEMI-ACTIVE SUSPENSION SYSTEMS BASED ON IMPROVED GENETIC ALGORITHMS

作　　者：高瑞贞[1] 张京军[1] 赵子月[1] 孙扬[1] 

机构地区：[1]河北工程大学机电工程学院,河北邯郸056038

出　　处：《工程力学》2012年第1期240-248,共9页Engineering Mechanics

基　　金：国家自然科学基金项目(60875037);河北省自然科学基金项目(E2008000731)

摘　　要：该文利用ADAMS软件建立了汽车半主动悬架系统多体模型,通过ADAMS/Control模块将悬架模型从ADAMS/View中导入MATLAB/Simulink环境中,然后,完成模糊控制器的设计。模糊控制器的模糊规则由Matlab语言编写的改进遗传算法进行优化,实现汽车半主动悬架系统多体模型模糊控制器的改进遗传算法优化设计。为了检验模糊控制器的控制效果和改进遗传算法的优化性能,在C级路面下,以25m/s和35m/s两种不同车速对半主动悬架系统和被动悬架系统进行对比分析。仿真结果表明:基于改进遗传算法的半主动悬架系统模糊控制能够显著改善汽车的行驶平顺性。This paper uses ADAMS software to establish a multi-body model of a semi-active suspension system. The suspension model is imported into MATLAB/Simulink from ADAMS/View by ADAMS/Control module, and then, a fuzzy logic controller is completed in MATLAB/Simulink environment. The fuzzy rules of controller are optimized by an improved genetic algorithm written in Matlab language, and that accomplishes the optimization design for the semi-active suspension systems based on improved genetic algorithms. In order to test the control efforts and the performance of the improved genetic algorithm, the semi-active suspension system is analyzed with random road profile at two different speeds, 25m/s and 35rn/s, by the comparison with the passive suspension. The results show that the fuzzy logic controller based on improved genetic algorithm enhances the ride comfort performance of the vehicle significantly.

关 键 词：半主动悬架 多体模型 模糊控制器 改进遗传算法 优化设计 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]