Intelligence-based vehicle active suspension adaptive control systems

Jiangtao Cao; Ping Li; Honghai Liu

doi:10.1049/PBCE092E_ch2

Intelligence-based vehicle active suspension adaptive control systems

Jiangtao Cao
, Ping Li
, Honghai Liu

Northwestern Polytechnical University Xian
University of Portsmouth
Liaoning University of Petroleum and Chemical Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

This chapter reviews computational-intelligence-involved approaches in active vehicle suspension control systems with a focus on the problems raised in practical implementations by their nonlinear and uncertain properties. After a brief introduction on active suspension models, the chapter explores state-of-the-art in fuzzy inference systems, neural networks, genetic algorithms, and their combination for suspension control issues. Discussion and comments are provided based on the reviewed simulation and experimental results. The chapter is concluded with remarks and future directions.

Original language	English
Title of host publication	Handbook of Vehicle Suspension Control Systems
Publisher	Institution of Engineering and Technology
Pages	39-67
Number of pages	29
ISBN (Electronic)	9781849196345
ISBN (Print)	9781849196338
DOIs	https://doi.org/10.1049/PBCE092E_ch2
State	Published - 1 Jan 2013
Externally published	Yes

Keywords

Adaptive control
Computational-intelligence-involved approach
Fuzzy inference systems
Fuzzy reasoning
Genetic algorithms
Genetic algorithms
Intelligence-based vehicle active suspension adaptive control systems
Intelligent control
Mechanical variables control
Neural nets
Neural networks
Nonlinear properties
Suspensions (mechanical components)
Uncertain properties

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10.1049/PBCE092E_ch2

Cite this

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title = "Intelligence-based vehicle active suspension adaptive control systems",

abstract = "This chapter reviews computational-intelligence-involved approaches in active vehicle suspension control systems with a focus on the problems raised in practical implementations by their nonlinear and uncertain properties. After a brief introduction on active suspension models, the chapter explores state-of-the-art in fuzzy inference systems, neural networks, genetic algorithms, and their combination for suspension control issues. Discussion and comments are provided based on the reviewed simulation and experimental results. The chapter is concluded with remarks and future directions.",

keywords = "Adaptive control, Computational-intelligence-involved approach, Fuzzy inference systems, Fuzzy reasoning, Genetic algorithms, Genetic algorithms, Intelligence-based vehicle active suspension adaptive control systems, Intelligent control, Mechanical variables control, Neural nets, Neural networks, Nonlinear properties, Suspensions (mechanical components), Uncertain properties",

author = "Jiangtao Cao and Ping Li and Honghai Liu",

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doi = "10.1049/PBCE092E\_ch2",

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AU - Li, Ping

AU - Liu, Honghai

N1 - Publisher Copyright: © The Institution of Engineering and Technology 2014.

PY - 2013/1/1

Y1 - 2013/1/1

N2 - This chapter reviews computational-intelligence-involved approaches in active vehicle suspension control systems with a focus on the problems raised in practical implementations by their nonlinear and uncertain properties. After a brief introduction on active suspension models, the chapter explores state-of-the-art in fuzzy inference systems, neural networks, genetic algorithms, and their combination for suspension control issues. Discussion and comments are provided based on the reviewed simulation and experimental results. The chapter is concluded with remarks and future directions.

AB - This chapter reviews computational-intelligence-involved approaches in active vehicle suspension control systems with a focus on the problems raised in practical implementations by their nonlinear and uncertain properties. After a brief introduction on active suspension models, the chapter explores state-of-the-art in fuzzy inference systems, neural networks, genetic algorithms, and their combination for suspension control issues. Discussion and comments are provided based on the reviewed simulation and experimental results. The chapter is concluded with remarks and future directions.

KW - Adaptive control

KW - Computational-intelligence-involved approach

KW - Fuzzy inference systems

KW - Fuzzy reasoning

KW - Genetic algorithms

KW - Intelligence-based vehicle active suspension adaptive control systems

KW - Intelligent control

KW - Mechanical variables control

KW - Neural nets

KW - Neural networks

KW - Nonlinear properties

KW - Suspensions (mechanical components)

KW - Uncertain properties

UR - https://www.scopus.com/pages/publications/85014271255

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DO - 10.1049/PBCE092E_ch2

M3 - 章节

AN - SCOPUS:85014271255

SN - 9781849196338

SP - 39

EP - 67

BT - Handbook of Vehicle Suspension Control Systems

PB - Institution of Engineering and Technology

ER -

Intelligence-based vehicle active suspension adaptive control systems

Abstract

Keywords

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