FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles

This study presents a field-programmable gate array (FPGA)-based mechatronic design and real-time fuzzy control method with computational intelligence optimization for omni-Mecanum-wheeled autonomous vehicles. With the advantages of cuckoo search (CS), an evolutionary CS-based fuzzy system is propos...

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Main Authors: Hsu-Chih Huang, Chin-Wang Tao, Chen-Chia Chuang, Jing-Jun Xu
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/8/11/1328
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spelling doaj-2562df9db76a4c569c6538875691b4602020-11-25T01:55:55ZengMDPI AGElectronics2079-92922019-11-01811132810.3390/electronics8111328electronics8111328FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous VehiclesHsu-Chih Huang0Chin-Wang Tao1Chen-Chia Chuang2Jing-Jun Xu3Department of Electrical Engineering, National Ilan University, Yilan 26047, TaiwanDepartment of Electrical Engineering, National Ilan University, Yilan 26047, TaiwanDepartment of Electrical Engineering, National Ilan University, Yilan 26047, TaiwanDepartment of Electrical Engineering, National Ilan University, Yilan 26047, TaiwanThis study presents a field-programmable gate array (FPGA)-based mechatronic design and real-time fuzzy control method with computational intelligence optimization for omni-Mecanum-wheeled autonomous vehicles. With the advantages of cuckoo search (CS), an evolutionary CS-based fuzzy system is proposed, called CS-fuzzy. The CS’s computational intelligence was employed to optimize the structure of fuzzy systems. The proposed CS-fuzzy computing scheme was then applied to design an optimal real-time control method for omni-Mecanum-wheeled autonomous vehicles with four wheels. Both vehicle model and CS-fuzzy optimization are considered to achieve intelligent tracking control of Mecanum mobile vehicles. The control parameters of the Mecanum fuzzy controller are online-adjusted to provide real-time capability. This methodology outperforms the traditional offline-tuned controllers without computational intelligences in terms of real-time control, performance, intelligent control and evolutionary optimization. The mechatronic design of the experimental CS-fuzzy based autonomous mobile vehicle was developed using FPGA realization. Some experimental results and comparative analysis are discussed to examine the effectiveness, performance, and merit of the proposed methods against other existing approaches.https://www.mdpi.com/2079-9292/8/11/1328computational intelligenceevolutionaryreal-timemecanum vehicle
collection DOAJ
language English
format Article
sources DOAJ
author Hsu-Chih Huang
Chin-Wang Tao
Chen-Chia Chuang
Jing-Jun Xu
spellingShingle Hsu-Chih Huang
Chin-Wang Tao
Chen-Chia Chuang
Jing-Jun Xu
FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles
Electronics
computational intelligence
evolutionary
real-time
mecanum vehicle
author_facet Hsu-Chih Huang
Chin-Wang Tao
Chen-Chia Chuang
Jing-Jun Xu
author_sort Hsu-Chih Huang
title FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles
title_short FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles
title_full FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles
title_fullStr FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles
title_full_unstemmed FPGA-Based Mechatronic Design and Real-Time Fuzzy Control with Computational Intelligence Optimization for Omni-Mecanum-Wheeled Autonomous Vehicles
title_sort fpga-based mechatronic design and real-time fuzzy control with computational intelligence optimization for omni-mecanum-wheeled autonomous vehicles
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2019-11-01
description This study presents a field-programmable gate array (FPGA)-based mechatronic design and real-time fuzzy control method with computational intelligence optimization for omni-Mecanum-wheeled autonomous vehicles. With the advantages of cuckoo search (CS), an evolutionary CS-based fuzzy system is proposed, called CS-fuzzy. The CS’s computational intelligence was employed to optimize the structure of fuzzy systems. The proposed CS-fuzzy computing scheme was then applied to design an optimal real-time control method for omni-Mecanum-wheeled autonomous vehicles with four wheels. Both vehicle model and CS-fuzzy optimization are considered to achieve intelligent tracking control of Mecanum mobile vehicles. The control parameters of the Mecanum fuzzy controller are online-adjusted to provide real-time capability. This methodology outperforms the traditional offline-tuned controllers without computational intelligences in terms of real-time control, performance, intelligent control and evolutionary optimization. The mechatronic design of the experimental CS-fuzzy based autonomous mobile vehicle was developed using FPGA realization. Some experimental results and comparative analysis are discussed to examine the effectiveness, performance, and merit of the proposed methods against other existing approaches.
topic computational intelligence
evolutionary
real-time
mecanum vehicle
url https://www.mdpi.com/2079-9292/8/11/1328
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