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Research Papers

Hybrid Fuzzy Skyhook Surface Control Using Multi-Objective Microgenetic Algorithm for Semi-Active Vehicle Suspension System Ride Comfort Stability Analysis

[+] Author and Article Information
Yi Chen1

School of Mechatronics Engineering,  University of Electronic Science and Technology of China, Chengdu 611731, Chinaleo.chen.yi@live.co.uk

Zhong-Lai Wang

School of Mechatronics Engineering,  University of Electronic Science and Technology of China, Chengdu 611731, Chinawzhonglai@uestc.edu.cn

Jing Qiu

School of Mechatronics Engineering,  University of Electronic Science and Technology of China, Chengdu 611731, Chinaqiujing@uestc.edu.cn

Hong-Zhong Huang

School of Mechatronics Engineering,  University of Electronic Science and Technology of China, Chengdu 611731, Chinahzhuang@uestc.edu.cn

1

Corresponding author.

J. Dyn. Sys., Meas., Control 134(4), 041003 (May 02, 2012) (14 pages) doi:10.1115/1.4006220 History: Received April 15, 2010; Revised February 12, 2012; Published April 30, 2012; Online May 02, 2012

A polynomial function supervising fuzzy sliding mode control (PSFαSMC), which embedded with skyhook surface method, is proposed for the ride comfort of a vehicle semi-active suspension. The multi-objective microgenetic algorithm (MOμGA) has been utilized to determine the PSFαSMC controller’s parameter alignment in a training process with three ride comfort objectives for the vehicle semi-active suspension, which is called the “offline” step. Then, the optimized parameters are applied to the real-time control process by the polynomial function supervising controller, which is named “online” step. A two-degree-of-freedom dynamic model of the vehicle semi-active suspension systems with the stability analysis is given for passenger’s ride comfort enhancement studies, and a simulation with the given initial conditions has been devised in MATLAB . The numerical results have shown that this hybrid control method is able to provide real-time enhanced level of reliable ride comfort performance for the semi-active suspension system.

Copyright © 2012 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

Passive, semi-active, and active suspension systems

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Figure 2

Two-degree-of-freedom semi-active suspension system

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Figure 3

Block diagram for the two-degree-of-freedom semi-active suspension system

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Figure 4

Ideal skyhook damper definition, adopted from Karnopp [2]

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Figure 5

Sliding mode surface with skyhook scheme [39-43]

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Figure 6

Sliding surface generation with skyhook scheme [11,40-44]

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Figure 7

Fuzzy logic controller architecture [43]

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Figure 8

The fuzzy inference system for 2-DOF SA suspension system

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Figure 9

FαSMC flow diagram

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Figure 10

Microgenetic algorithm for PSFαSMC work flow diagram

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Figure 11

PSFαSMC offline step—training

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Figure 12

PSFαSMC online step—control for SA suspension system

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Figure 13

Uncertainty analysis framework for vehicle suspension system ride comfort

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Figure 14

Polynomial supervising functions of PSFαSMC parameters for ride comfort control

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Figure 15

Fitness functions—J1 , J2 , and J3

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Figure 16

Vehicle body acceleration y1 response in time domain

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Figure 17

Tyre load response y2 in time domain

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Figure 18

Suspension deformation y3 response in time domain

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Figure 19

Vehicle body acceleration response in frequency domain

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Figure 20

Vehicle body response phase plot

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Figure 21

Sliding surface switching plot

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