半主动悬架系统振动控制的模糊小脑模型关节控制器(FCMAC)

16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06) Pub Date : 2006-11-29 DOI:10.1109/ICAT.2006.67

Shiming Wang

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引用次数: 0

摘要

基于Buckingham ' s Pi理论，建立了半主动客车悬架的物理模型。根据系统的特点，提出了一种基于模糊逻辑控制和小脑模型衔接控制技术的智能控制算法——模糊小脑模型衔接控制(FCMAC)，并首次用于在线控制，推导了保证闭环系统稳定性的权重更新规律，用矩阵形式的代数方程描述了信息检索和学习规则。三种典型振动信号激励下的闭环实验结果表明，与PID等传统控制策略相比，FCMAC控制策略可使半主动悬架系统垂直加速度均方根值降低23%、25%和18%。

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Fuzzy Cerebellar Model Articulation Controller (FCMAC) for Vibration Control of Semi-Active Suspension System

The physical model of semi-active quarter-coach suspension was established based on the theories of Buckingham s Pi. According to the characteristics of system, a new intelligent control algorithm based on the fuzzy logic control and cerebellar model articulation control techniques-fuzzy cerebellar model articulation control (FCMAC) was presented and used to perform online control for the first time, novel weight-update laws were derived that guarantee the stability of closed-loop system, both information retrieval and learning rules were described by algebraic equations in matrix form. The results of experiment of closed-loop excited by three typical vibration signals showed that FCMAC control strategy can reduce the value of mean square root of vertical acceleration of semi-active suspension system to be lower 23%, 25% and 18% compared with the traditional control strategy such as PID.

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16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06)

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