Active suspension control based on adaptive wavelets neuro-fuzzy strategy

L. Khan, S. Qamar, M. U. Khan
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引用次数: 1

Abstract

The main objective of this paper is to obtain improved active suspension control for the full car model. The conventional passive suspension and semi-active suspension systems do not provide passenger comfort and vehicle handling against the road disturbances. To tackle this problem, an adaptive wavelets neuro-fuzzy (AWNF) based control strategy is used for active suspension control. The AWNF control has the robustness abilities and good generalization properties. The performance of the active suspension system is determined by the displacement and acceleration of the vehicle. To validate the effectiveness of the proposed control scheme, the full car model is simulated in MATLAB/Simulink and subjected to a varying road profile. The performance of the AWNF based active suspension system is compared with passive and semi-active suspension system.
基于自适应小波神经模糊策略的悬架主动控制
本文的主要目标是对全车模型进行改进的主动悬架控制。传统的被动悬架和半主动悬架系统不能提供乘客舒适性和车辆对道路干扰的处理。为了解决这一问题,提出了一种基于自适应小波神经模糊(AWNF)的主动悬架控制策略。AWNF控制具有鲁棒性和良好的泛化性能。主动悬架系统的性能取决于车辆的位移和加速度。为了验证所提出的控制方案的有效性,在MATLAB/Simulink中对整车模型进行了仿真,并进行了不同道路轮廓的仿真。将基于AWNF的主动悬架系统与被动悬架和半主动悬架系统的性能进行了比较。
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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