Please use this identifier to cite or link to this item: http://ddms.usim.edu.my:80/jspui/handle/123456789/8735
Title: Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
Authors: Y.M., Sam,
Z., Mohamed,
M., Khairi Aripin,
M., Fahezal Ismail,
L., Ramli,
Keywords: Active front steering system
Composite nonlinear feedback
MOPSO
Multiple objective
Optimal controller
Optimization
Particle swarm optimization
Issue Date: 2015
Publisher: Penerbit UTM Press
Abstract: The purpose of controlling the vehicle handling is to ensure that the vehicle is in a safe condition and following its desire path. Vehicle yaw rate is controlled in order to achieve a good vehicle handling. In this paper, the optimal Composite Nonlinear Feedback (CNF) control technique is proposed for an Active Front Steering (AFS) system for improving the vehicle yaw rate response. The model used in order to validate the performance of controller is nonlinear vehicle model with 7 degree-of-freedom (DOF) and a bicycle model is implemented for the purpose of designing the controller. In designing an optimal CNF controller, the parameter estimation of linear and nonlinear gain becomes very important to produce the best output response. An intelligent algorithm is designed to minimize the time consumed to get the best parameter. To design an optimal method, Multi Objective Particle Swarm Optimization (MOPSO) is utilized to optimize the CNF controller performance. As a result, transient performance of the yaw rate has improved with the increased speed of in tracking and searching of the best optimized parameter estimation for the linear and the nonlinear gain of CNF controller.
URI: http://ddms.usim.edu.my/handle/123456789/8735
ISSN: 1279696
Appears in Collections:Jurnal Teknologi (Sciences and Engineering)

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