A Fuzzy Control Method in ACC of the Constant Interval Mode

Lai Gang Zhao; Dao Jiong Chen

doi:10.4028/www.scientific.net/AMR.201-203.2083

Paper Titles

Hardware-in-the-Loop Simulation System in the Development of Temperature Controller of Plastic Extruder
p.2063

Infinite AdaBoost and its Application on Fault Diagnosis for Analog Circuits
p.2070

Performance Analysis of W Phase Detector in Galileo Signal Receiver
p.2075

The Research on the Model of a Precision Magnetic Stage System
p.2079

A Fuzzy Control Method in ACC of the Constant Interval Mode
p.2083

Study of Predictive Control in Industrial Networked Control System
p.2087

Construction and Realization of Networked Virtual Test System Based on LabVIEW
p.2091

The Application of FPGA and DSP Techniques in Intelligent Wattmeter
p.2096

Analysis and Modeling of the Harmonic Compensation Errors Based on PWM Converters
p.2101

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 201-203A Fuzzy Control Method in ACC of the Constant...

A Fuzzy Control Method in ACC of the Constant Interval Mode

Abstract:

Fuzzy control methods are widely used in Adaptive Cruise Control System as time passes by,but there are also various limitations for its membership and fuzzy rule acquisition, over-relying on experts’ knowledge. This paper presented one Sugeno method based on Mamdani using ANFIS(adaptive network-based fuzzy inference system)with optimized its memberships and training processes. Its experimental results revealed that it can be embeded into ACC much more appropriately and efficiently.

You might also be interested in these eBooks

Advanced Manufacturing Systems, ICMSE 2011

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 201-203)

Pages:

2083-2086

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.201-203.2083

Citation:

Cite this paper

Online since:

February 2011

Authors:

Lai Gang Zhao, Dao Jiong Chen

Keywords:

Adaptive Cruise Control System, Adaptive Network-Based Fuzzy Inference System, Fuzzy Method, MATLAB, Sugeno System

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] HironoriMiyakoshi, Nobuyuki Furui, TsuneoMiyakoshi, etal. Development of adap tive cruise control system[ J ]. TOYOTA Technical Review, 1999, 48 (2) : 24 - 27.

Google Scholar

[2] Zhonghai Liu. Designing and simulation for adaptive cruise control systems [D]. TsingHua University Press, (2005).

Google Scholar

[3] Defeng Zhang. Modeling and Simulation examples for MATLAB/SIMULINK[M]. Mechanical Industry Press. (2010).

Google Scholar

[4] Defeng Zhang. Fuzzy system design for MATLAB[M]. National Defense Industrial Press. (2009).

Google Scholar

[5] Defeng Zhang. Neural-Network design for MATLAB[M]. Mechanical Industry Press. (2010).

Google Scholar

[6] China Forum for MATLAB. Concrete examples of neural-network in MATLAB[M]. Beijing University of Aeronautics And Astro-nautics Press. (2010).

Google Scholar

[7] Qige Ye, Jie Wu. One self-organizing fuzzy-neural network controller. Control And Decision. (1998).

Google Scholar

[8] Zhifeng Jiang, Zemin Liu. Research on a new-type fuzzy-neural network. Journal of Circuits and Systems. (1997).

Google Scholar