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...
| Main Authors: | , , |
|---|---|
| Format: | Proceeding Paper |
| 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/79633/1/79633_Velocity%20Control%20for%20Spherical%20_complete.pdf http://irep.iium.edu.my/79633/2/79633_Velocity%20Control%20for%20Spherical%20_scopus.pdf |
| _version_ | 1848788805208768512 |
|---|---|
| author | Kamis, Nurul Nafisah Embong, Abd. Halim Ahmad, Salmiah |
| author_facet | Kamis, Nurul Nafisah Embong, Abd. Halim Ahmad, Salmiah |
| author_sort | Kamis, Nurul Nafisah |
| building | IIUM Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T17:46:39Z |
| format | Proceeding Paper |
| id | iium-79633 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:46:39Z |
| publishDate | 2019 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-796332020-07-07T08:17:51Z 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 Proceeding Paper 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, Selangor. https://ieeexplore-ieee-org.ezproxy.um.edu.my/stamp/stamp.jsp?tp=&arnumber=8825075 10.1109/I2CACIS.2019.8825075 |
| 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 |
| title | 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_short | Velocity control for spherical robot using PI-fuzzy logic |
| title_sort | velocity control for spherical robot using pi-fuzzy logic |
| topic | T Technology (General) TJ210.2 Mechanical devices and figures. Automata. Ingenious mechanism. Robots (General) |
| 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 |