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CONSTRUCTION OF STEERING AND SUSPENSION SYSTEMS OF CARMODELS USING FUZZY REASONING

利用模糊推理构建轿车转向和悬架系统

基本信息

批准号：
13650254
负责人：
YOSHIMURA Toshio
金额：
$ 2.24万
依托单位：
The University of Tokushima
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2001
资助国家：
日本
起止时间：
2001 至 2003
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-13650254/
关键词：
INTELLIGENT TRASPORTATION SYSTEM STEERING CONTROL SUSPENSION CONTROL DISTURBANCE QBSERVER CAR MODEL FUZZY CONTROL SIMULATION RIDE COMFORT フィードバック制御スカイフックダンパー制御

项目摘要

Recently, automatic driving control for intelligent transportation systems becomes the important role in increasing traffic and reliving driver's load. The investigation is concerned with the construction of the steering control for car models so as to maintain the vehicle current position for the desired course by steering angles. However, the safety and ride comfort of passengers is less improved by the larger difference as the control force becomes stranger. Therefore, the steering control problem is coupled with the suspension control problem. The purpose of this paper is to propose the development of a steering and suspension system of a full car model subject to the side force of wind and the excitation from a road profile. As the vehicle dynamics are practically described by a complicated system including the effect of non-linearity and uncertainty, the steering control of front/rear and right/left wheel angles, and the suspension controls at front/rear and right/left wheel loca … More tions are respectively determined by using fuzzy reasoning. However, the control structure becomes more complicated as the number of fuzzy control rules more increases exponentially if the number of the variables in the precondition part more increases. The fuzzy reasoning by single input rule modules to decrease the number of fuzzy control rules is proposed where the fuzzy control rules are expressed as a set of single variable in the precondition and conclusion parts. The investigation has been proposed for a half car model at the first stage, and secondly it has been extended to a full car model. The side force of wind and the excitation from the road profile have been estimated by using disturbance observers, and the steering angles have been determined by using the forward control derived from the disturbance observer for the side force of wind and the feedback control derived from fuzzy reasoning. The simulation result indicates that the proposed steering and suspension system is very effective in the performance of vehicle maneuverability and ride comfort Less

近年来，智能交通系统的自动驾驶控制在增加交通量、减轻驾驶员负担方面发挥着重要作用。该研究涉及汽车模型的转向控制结构，以便通过转向角保持车辆当前位置以实现所需的路线。然而，由于控制力变得陌生，较大的差异对乘客的安全性和乘坐舒适性的改善较小。因此，转向控制问题与悬架控制问题耦合在一起。本文的目的是提出开发一种能够承受侧风力和路面激励的整车模型的转向和悬架系统。由于车辆动力学实际上是由一个复杂的系统来描述，包括非线性和不确定性的影响，前/后和右/左轮角度的转向控制，以及前/后和右/左轮位置的悬架控制分别通过模糊推理来确定。然而，如果前置条件部分中的变量数量越多，则随着模糊控制规则的数量呈指数增加，控制结构变得更加复杂。提出了通过单输入规则模块进行模糊推理以减少模糊控制规则的数量，其中模糊控制规则在前提和结论部分表示为一组单变量。第一阶段提出针对半车车型进行调查，其次扩大至全车车型。利用扰动观测器估计风的侧向力和道路轮廓的激励，并利用风侧向力扰动观测器导出的前向控制和模糊推理导出的反馈控制来确定转向角。仿真结果表明，所提出的转向和悬架系统在车辆操纵性和乘坐舒适性方面表现非常有效。