实验性主动悬架系统自适应神经模糊推理系统的设计与实现

V. Hari, P. Lakshmi, R. Kalaivani
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引用次数: 3

摘要

本文介绍了一种实验性主动悬架系统(ASS)的自适应神经模糊推理系统(ANFIS)和传统的比例、积分和导数(PID)控制器的设计与实现,以提高乘客的乘坐舒适性。如何有效地控制车辆的平顺性和操控性能是主动悬架系统面临的挑战,特别是在不平整的道路上。一般来说,崎岖不平的道路会给车内的人带来不适,也会损坏车辆的电子和机械部件。因此,一个良好的调校悬架系统是更重要的,以提高乘客的舒适性。通过LabVIEW软件设计并实现了PID控制器和ANFIS控制器的实时整定。通过对两种控制器的时间响应进行比较,结果表明,采用ANFIS的系统能显著降低簧载质量位移和车身加速度,从而提高车辆的平顺性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and implementation of Adaptive Neuro Fuzzy Inference System for an experimental Active Suspension System
This paper describes the design and implementation of the Adaptive Neuro Fuzzy Inference System (ANFIS) and the conventional Proportional, Integral and Derivative (PID) controller for an experimental Active Suspension System (ASS) in order to improve the travelling comfort of the passengers. Effective control of ride quality and handling performance are challenges for active vehicle suspension systems, particularly for road with irregularities. Generally a bumpy road creates discomfort to the human beings in the vehicle and damages to the vehicle's electronic and mechanical components. Hence a well-tuned suspension system is more important to enhance the comfort of the passengers. The PID and ANFIS controllers have been designed and implemented to the real time setup through the LabVIEW software. Comparison between the time responses with both the controllers has been carried out and it shows that, the system with ANFIS gives significant reduction of the sprung mass displacement and body acceleration and thus improves the vehicle ride comfort.
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