Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm
This paper presents the identification of the Thermoelectric Cooler (TEC) plant using a novel metaheuristic called hybrid Multi-Verse Optimizer with Sine Cosine Algorithm (hMVOSCA) based continuous-time Hammerstein model. In the identification, a continuous-time linear system is used, which is more...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2021
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| Online Access: | https://umpir.ump.edu.my/id/eprint/33294/ |
| _version_ | 1848827297113571328 |
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| author | Jui, Julakha Jahan Mohd Ashraf, Ahmad Mohamed Sultan, Mohamed Ali Mohd Anwar, Zawawi Mohd Falfazli, Mat Jusof |
| author_facet | Jui, Julakha Jahan Mohd Ashraf, Ahmad Mohamed Sultan, Mohamed Ali Mohd Anwar, Zawawi Mohd Falfazli, Mat Jusof |
| author_sort | Jui, Julakha Jahan |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | This paper presents the identification of the Thermoelectric Cooler (TEC) plant using a novel metaheuristic called hybrid Multi-Verse Optimizer with Sine Cosine Algorithm (hMVOSCA) based continuous-time Hammerstein model. In the identification, a continuous-time linear system is used, which is more suitable for representing any real plant. The hMVOSCA algorithm is used to reduce the gap between estimated and actual output by identifying the coefficients of both the linear and the nonlinear Hammerstein model subsystems. Efficiency of the hMVOSCA algorithm also evaluated based on the convergence curve, bode plot of the linear subsystem, function plot of the nonlinear subsystem, and statistical performance value. The results demonstrate that the proposed hMVOSCA algorithm can produce the Hammerstein model that generates an estimated output like the actual TEC output. Moreover, the identified outputs also show that the hMVOSCA algorithm outperforms the conventional metaheuristic algorithms such as MVO and SCA by balancing exploration and exploitation and low searching capability. |
| first_indexed | 2025-11-15T03:58:28Z |
| format | Conference or Workshop Item |
| id | ump-33294 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:58:28Z |
| publishDate | 2021 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-332942025-10-23T01:53:17Z https://umpir.ump.edu.my/id/eprint/33294/ Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm Jui, Julakha Jahan Mohd Ashraf, Ahmad Mohamed Sultan, Mohamed Ali Mohd Anwar, Zawawi Mohd Falfazli, Mat Jusof TK Electrical engineering. Electronics Nuclear engineering This paper presents the identification of the Thermoelectric Cooler (TEC) plant using a novel metaheuristic called hybrid Multi-Verse Optimizer with Sine Cosine Algorithm (hMVOSCA) based continuous-time Hammerstein model. In the identification, a continuous-time linear system is used, which is more suitable for representing any real plant. The hMVOSCA algorithm is used to reduce the gap between estimated and actual output by identifying the coefficients of both the linear and the nonlinear Hammerstein model subsystems. Efficiency of the hMVOSCA algorithm also evaluated based on the convergence curve, bode plot of the linear subsystem, function plot of the nonlinear subsystem, and statistical performance value. The results demonstrate that the proposed hMVOSCA algorithm can produce the Hammerstein model that generates an estimated output like the actual TEC output. Moreover, the identified outputs also show that the hMVOSCA algorithm outperforms the conventional metaheuristic algorithms such as MVO and SCA by balancing exploration and exploitation and low searching capability. Institute of Electrical and Electronics Engineers Inc. 2021 Conference or Workshop Item PeerReviewed pdf en https://umpir.ump.edu.my/id/eprint/33294/1/Thermoelectric%20cooler%20identification%20based%20on%20continuous-time_FULL.pdf Jui, Julakha Jahan and Mohd Ashraf, Ahmad and Mohamed Sultan, Mohamed Ali and Mohd Anwar, Zawawi and Mohd Falfazli, Mat Jusof (2021) Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm. In: Proceedings - 2021 International Conference on Software Engineering and Computer Systems and 4th International Conference on Computational Science and Information Management, ICSECS-ICOCSIM 2021. 7th International Conference on Software Engineering and Computer Systems and 4th International Conference on Computational Science and Information Management, ICSECS-ICOCSIM 2021 , 24 August 2021 - 26 August 2021 , Virtual, Pekan. pp. 556 -561. (171807). ISBN 978-166541407-4 (Published) https://doi.org/10.1109/ICSECS52883.2021.00108 https://10.2478/cait-2021-0036 https://10.2478/cait-2021-0036 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Jui, Julakha Jahan Mohd Ashraf, Ahmad Mohamed Sultan, Mohamed Ali Mohd Anwar, Zawawi Mohd Falfazli, Mat Jusof Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm |
| title | Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm |
| title_full | Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm |
| title_fullStr | Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm |
| title_full_unstemmed | Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm |
| title_short | Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm |
| title_sort | thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | https://umpir.ump.edu.my/id/eprint/33294/ https://umpir.ump.edu.my/id/eprint/33294/ https://umpir.ump.edu.my/id/eprint/33294/ |