PID-Ant Colony Optimization (ACO) control for electric power assist steering system for electric vehicle

Electric Power Assist Steering (EPAS) system offers a significant potential in enhancing the driving performance of a vehicle where the energy conserving issue is important. In this paper, Ant Colony Optimization (ACO) algorithm is implemented as tuning mechanism for PID controller. The aim of...

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Bibliographic Details
Main Authors: Abu Hanifah, Rabiatuladawiyah, Toha, Siti Fauziah, Ahmad, Salmiah
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
Online Access:http://irep.iium.edu.my/34112/
http://irep.iium.edu.my/34112/1/ICSIMA-epas_DR_Fauziah_MCT.pdf
Description
Summary:Electric Power Assist Steering (EPAS) system offers a significant potential in enhancing the driving performance of a vehicle where the energy conserving issue is important. In this paper, Ant Colony Optimization (ACO) algorithm is implemented as tuning mechanism for PID controller. The aim of this hybrid controller is to minimize energy consumption of the EPAS system in Electric Vehicle (EV) by minimizing the assist current supplied to the assist motor. The ACO algorithm searching technique is applied to search for the best gain parameters of the PID controller. The fast tuning feature of ACO algorithm is the factor that distinguish this hybrid method as compared to conventional trial and error method PID controller tuning. Simulation results shows the performance and effectiveness of using ACO algorithm for PID tuning.