A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control

Due to the complexity of autonomous mobile robot’s requirement and drastic technological changes, the safe and efficient path tracking development is becoming complex and requires intensive knowledge and information, thus the demand for advanced algorithm has rapidly increased. Analyzing unstructure...

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Main Authors: Razali, Muhammad Razmi, Mohd. Faudzi, Ahmad Athif, Shamsudin, Abu Ubaidah, Mohamaddan, Shahrol
Format: Article
Language:English
Published: Frontiers Media S.A. 2023
Subjects:
Online Access:http://eprints.utm.my/107458/1/AhmadAthifMohdFaudzi2023_AHybridControllerMethodWithGeneticAlgorithm.pdf
http://eprints.utm.my/107458/
http://dx.doi.org/10.3389/frobt.2022.1087371
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Institution: Universiti Teknologi Malaysia
Language: English
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spelling my.utm.1074582024-09-18T06:31:34Z http://eprints.utm.my/107458/ A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control Razali, Muhammad Razmi Mohd. Faudzi, Ahmad Athif Shamsudin, Abu Ubaidah Mohamaddan, Shahrol TK Electrical engineering. Electronics Nuclear engineering Due to the complexity of autonomous mobile robot’s requirement and drastic technological changes, the safe and efficient path tracking development is becoming complex and requires intensive knowledge and information, thus the demand for advanced algorithm has rapidly increased. Analyzing unstructured gain data has been a growing interest among researchers, resulting in valuable information in many fields such as path planning and motion control. Among those, motion control is a vital part of a fast, secure operation. Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. Therefore, this research aims to design a new gain optimization approach to assist researcher in identifying the value of the gain’s product with a qualitative comparative study of the up-to-date controllers. Gains optimization in this context is to classify the near perfect value of the gain’s product and processes. For this, a domain controller will be developed based on the attributes of the Fuzzy-PID parameters. The development of the Fuzzy Logic Controller requires information on the PID controller parameters that will be fuzzified and defuzzied based on the resulting 49 fuzzy rules. Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). It is expected that the domain controller will give a positive impact to the path planning position and angular PID controller algorithm that meet the autonomous demand. Frontiers Media S.A. 2023 Article PeerReviewed application/pdf en http://eprints.utm.my/107458/1/AhmadAthifMohdFaudzi2023_AHybridControllerMethodWithGeneticAlgorithm.pdf Razali, Muhammad Razmi and Mohd. Faudzi, Ahmad Athif and Shamsudin, Abu Ubaidah and Mohamaddan, Shahrol (2023) A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control. Frontiers in Robotics and AI, 9 (NA). pp. 1-14. ISSN 2296-9144 http://dx.doi.org/10.3389/frobt.2022.1087371 DOI : 10.3389/frobt.2022.1087371
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Razali, Muhammad Razmi
Mohd. Faudzi, Ahmad Athif
Shamsudin, Abu Ubaidah
Mohamaddan, Shahrol
A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
description Due to the complexity of autonomous mobile robot’s requirement and drastic technological changes, the safe and efficient path tracking development is becoming complex and requires intensive knowledge and information, thus the demand for advanced algorithm has rapidly increased. Analyzing unstructured gain data has been a growing interest among researchers, resulting in valuable information in many fields such as path planning and motion control. Among those, motion control is a vital part of a fast, secure operation. Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. Therefore, this research aims to design a new gain optimization approach to assist researcher in identifying the value of the gain’s product with a qualitative comparative study of the up-to-date controllers. Gains optimization in this context is to classify the near perfect value of the gain’s product and processes. For this, a domain controller will be developed based on the attributes of the Fuzzy-PID parameters. The development of the Fuzzy Logic Controller requires information on the PID controller parameters that will be fuzzified and defuzzied based on the resulting 49 fuzzy rules. Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). It is expected that the domain controller will give a positive impact to the path planning position and angular PID controller algorithm that meet the autonomous demand.
format Article
author Razali, Muhammad Razmi
Mohd. Faudzi, Ahmad Athif
Shamsudin, Abu Ubaidah
Mohamaddan, Shahrol
author_facet Razali, Muhammad Razmi
Mohd. Faudzi, Ahmad Athif
Shamsudin, Abu Ubaidah
Mohamaddan, Shahrol
author_sort Razali, Muhammad Razmi
title A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
title_short A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
title_full A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
title_fullStr A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
title_full_unstemmed A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
title_sort hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
publisher Frontiers Media S.A.
publishDate 2023
url http://eprints.utm.my/107458/1/AhmadAthifMohdFaudzi2023_AHybridControllerMethodWithGeneticAlgorithm.pdf
http://eprints.utm.my/107458/
http://dx.doi.org/10.3389/frobt.2022.1087371
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