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Genetic algorithm based fuzzy logic control for a magneto-rheological suspension

机译:基于遗传算法的磁流变悬架模糊逻辑控制

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摘要

To overcome the limitations of conventional fuzzy logic control strategies, an adaptive fuzzy logic control based on a hybrid Taguchi genetic algorithm is proposed to control the vibration of the magneto-rheological suspension in order to promote ride comfort. A half-car model equipped with two telescopic magneto-rheological dampers is first developed. An adaptive fuzzy logic control based on a hybrid Taguchi genetic algorithm is then formulated on the basis of the developed model. The hybrid Taguchi genetic algorithm is applied to tune the linguistic variables and control rules of the fuzzy logic control. Finally, a road test is carried out to validate the proposed control scheme. For comparison purposes, a conventional fuzzy logic control is also implemented on the test car. The results show that the magneto-rheological suspension system with two control strategies can improve ride comfort, and the proposed control algorithm has better ride improvement than conventional fuzzy logic control.
机译:为了克服传统模糊逻辑控制策略的局限性,提出了一种基于混合田口遗传算法的自适应模糊逻辑控制,以控制磁流变悬架的振动,以提高乘坐舒适性。首次开发了带有两个伸缩式磁流变阻尼器的半车模型。在此基础上,建立了基于混合田口遗传算法的自适应模糊逻辑控制。应用Taguchi混合遗传算法对模糊逻辑控制的语言变量和控制规则进行调整。最后,进行了路试以验证所提出的控制方案。为了比较,在测试车上也采用了常规的模糊逻辑控制。结果表明,具有两种控制策略的磁流变悬架系统可以提高乘坐舒适性,并且与常规模糊逻辑控制相比,该控制算法具有更好的乘坐改进。

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