Velocity control for spherical robot using PI-fuzzy logic

— This paper presents the finding on designing the fuzzy logic controller and analysis of the step input test on the model and control design. The PI-type fuzzy logic controller (FLC) was designed to control the velocity of the rolling spherical robot. The spherical robot model was tested with s...

Full description

Bibliographic Details
Main Authors: Kamis, Nurul Nafisah, Embong, Abd. Halim, Ahmad, Salmiah
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2019
Subjects:
Online Access:http://irep.iium.edu.my/79633/
http://irep.iium.edu.my/79633/
http://irep.iium.edu.my/79633/
http://irep.iium.edu.my/79633/1/79633_Velocity%20Control%20for%20Spherical%20_complete.pdf
http://irep.iium.edu.my/79633/2/79633_Velocity%20Control%20for%20Spherical%20_scopus.pdf
id iium-79633
recordtype eprints
spelling iium-796332020-03-19T02:29:32Z http://irep.iium.edu.my/79633/ Velocity control for spherical robot using PI-fuzzy logic Kamis, Nurul Nafisah Embong, Abd. Halim Ahmad, Salmiah T Technology (General) TJ210.2 Mechanical devices and figures. Automata. Ingenious mechanism. Robots (General) — This paper presents the finding on designing the fuzzy logic controller and analysis of the step input test on the model and control design. The PI-type fuzzy logic controller (FLC) was designed to control the velocity of the rolling spherical robot. The spherical robot model was tested with step input signal to analysis the effectiveness of the designed Fuzzy logic controller with 25-membership rule being constructed in Fuzzy toolbox MATLAB using triangular membership function and combination of gaussian and sigmoidal membership function. The output scaling factor (output gain) of FLC was tuned using Response Optimization toolbox and Particle Swarm Optimization to improve the system performance. Optimization using Matlab toolbox is done by specified the desired step response characteristics while in PSO, minimizing the Integral Absolute Error (IAE) is used as on objective of the optimization. The combined membership function shows better performance with less 8% overshoot, rise time less than 2s and settle at less than 3s after the response optimization process. Meanwhile, the PSO manage to tune the gain to reduce the IAE but contain large overshoot and longer settling time. Institute of Electrical and Electronics Engineers Inc. 2019-06 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/79633/1/79633_Velocity%20Control%20for%20Spherical%20_complete.pdf application/pdf en http://irep.iium.edu.my/79633/2/79633_Velocity%20Control%20for%20Spherical%20_scopus.pdf Kamis, Nurul Nafisah and Embong, Abd. Halim and Ahmad, Salmiah (2019) Velocity control for spherical robot using PI-fuzzy logic. In: "2019 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2019", 29 June 2019, Grand Blue Wave HotelSelangor. https://ieeexplore-ieee-org.ezproxy.um.edu.my/stamp/stamp.jsp?tp=&arnumber=8825075 10.1109/I2CACIS.2019.8825075
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
English
topic T Technology (General)
TJ210.2 Mechanical devices and figures. Automata. Ingenious mechanism. Robots (General)
spellingShingle T Technology (General)
TJ210.2 Mechanical devices and figures. Automata. Ingenious mechanism. Robots (General)
Kamis, Nurul Nafisah
Embong, Abd. Halim
Ahmad, Salmiah
Velocity control for spherical robot using PI-fuzzy logic
description — This paper presents the finding on designing the fuzzy logic controller and analysis of the step input test on the model and control design. The PI-type fuzzy logic controller (FLC) was designed to control the velocity of the rolling spherical robot. The spherical robot model was tested with step input signal to analysis the effectiveness of the designed Fuzzy logic controller with 25-membership rule being constructed in Fuzzy toolbox MATLAB using triangular membership function and combination of gaussian and sigmoidal membership function. The output scaling factor (output gain) of FLC was tuned using Response Optimization toolbox and Particle Swarm Optimization to improve the system performance. Optimization using Matlab toolbox is done by specified the desired step response characteristics while in PSO, minimizing the Integral Absolute Error (IAE) is used as on objective of the optimization. The combined membership function shows better performance with less 8% overshoot, rise time less than 2s and settle at less than 3s after the response optimization process. Meanwhile, the PSO manage to tune the gain to reduce the IAE but contain large overshoot and longer settling time.
format Conference or Workshop Item
author Kamis, Nurul Nafisah
Embong, Abd. Halim
Ahmad, Salmiah
author_facet Kamis, Nurul Nafisah
Embong, Abd. Halim
Ahmad, Salmiah
author_sort Kamis, Nurul Nafisah
title Velocity control for spherical robot using PI-fuzzy logic
title_short Velocity control for spherical robot using PI-fuzzy logic
title_full Velocity control for spherical robot using PI-fuzzy logic
title_fullStr Velocity control for spherical robot using PI-fuzzy logic
title_full_unstemmed Velocity control for spherical robot using PI-fuzzy logic
title_sort velocity control for spherical robot using pi-fuzzy logic
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2019
url http://irep.iium.edu.my/79633/
http://irep.iium.edu.my/79633/
http://irep.iium.edu.my/79633/
http://irep.iium.edu.my/79633/1/79633_Velocity%20Control%20for%20Spherical%20_complete.pdf
http://irep.iium.edu.my/79633/2/79633_Velocity%20Control%20for%20Spherical%20_scopus.pdf
first_indexed 2023-09-18T21:51:38Z
last_indexed 2023-09-18T21:51:38Z
_version_ 1777413807986966528