Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems
This paper suggests five new contributions with respect to the state-of-the-art. First, the optimal tuning of cost-effective fuzzy controllers represented by Takagi–Sugeno–Kang proportional-integral fuzzy controllers (TSK PI-FCs) is carried out using a fresh metaheuristic algorithm, namely the Slime...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2021-03-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/125954163/view |
| _version_ | 1817982949889409024 |
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| author | Radu-Emil Precup Radu-Codrut David Raul-Cristian Roman Emil M. Petriu Alexandra-Iulia Szedlak-Stinean |
| author_facet | Radu-Emil Precup Radu-Codrut David Raul-Cristian Roman Emil M. Petriu Alexandra-Iulia Szedlak-Stinean |
| author_sort | Radu-Emil Precup |
| collection | DOAJ |
| description | This paper suggests five new contributions with respect to the state-of-the-art. First, the optimal tuning of cost-effective fuzzy controllers represented by Takagi–Sugeno–Kang proportional-integral fuzzy controllers (TSK PI-FCs) is carried out using a fresh metaheuristic algorithm, namely the Slime Mould Algorithm (SMA), and a fuzzy controller tuning approach is offered. Second, a relatively easily understandable formulation of SMA is offered. Third, a real-world application of SMA is given, focusing on the optimal tuning of TSK PI-FCs for nonlinear servo systems in terms of optimization problems that target the minimization of discrete-time cost functions defined as the sum of time multiplied by squared control error. Fourth, using the concept of improving the performance of metaheuristic algorithms with information feedback models, proposed by Wang and Tan, Improving metaheuristic algorithms with information feedback models, IEEE Trans. Cybern. 49 (2019), 542–555, Gu and Wang, Improving NSGA-III algorithms with information feedback models for large-scale many-objective optimization, Fut. Gen. Comput. Syst. 107 (2020), 49–69, and Zhang et al., Enhancing MOEA/D with information feedback models for large-scale many-objective optimization, Inf. Sci. 522 (2020), 1–16, new metaheuristic algorithms are introduced in terms of inserting the model F1 in SMA and other representative algorithms, namely Gravitational Search Algorithm (GSA), Charged System Search (CSS), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA). Fifth, the real-time validation of the cost-effective fuzzy controllers and their tuning approach is performed in the framework of angular position control of laboratory servo system. The comparison with other metaheuristic algorithms that solve the same optimization problem for optimal parameter tuning of cost-effective fuzzy controllers suggestively highlights the superiority of SMA. Experimental results are included. |
| first_indexed | 2024-04-13T23:27:41Z |
| format | Article |
| id | doaj.art-2a45e6294daa45fba513046970c682c1 |
| institution | Directory Open Access Journal |
| issn | 1875-6883 |
| language | English |
| last_indexed | 2024-04-13T23:27:41Z |
| publishDate | 2021-03-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj.art-2a45e6294daa45fba513046970c682c12022-12-22T02:25:00ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832021-03-0114110.2991/ijcis.d.210309.001Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo SystemsRadu-Emil PrecupRadu-Codrut DavidRaul-Cristian RomanEmil M. PetriuAlexandra-Iulia Szedlak-StineanThis paper suggests five new contributions with respect to the state-of-the-art. First, the optimal tuning of cost-effective fuzzy controllers represented by Takagi–Sugeno–Kang proportional-integral fuzzy controllers (TSK PI-FCs) is carried out using a fresh metaheuristic algorithm, namely the Slime Mould Algorithm (SMA), and a fuzzy controller tuning approach is offered. Second, a relatively easily understandable formulation of SMA is offered. Third, a real-world application of SMA is given, focusing on the optimal tuning of TSK PI-FCs for nonlinear servo systems in terms of optimization problems that target the minimization of discrete-time cost functions defined as the sum of time multiplied by squared control error. Fourth, using the concept of improving the performance of metaheuristic algorithms with information feedback models, proposed by Wang and Tan, Improving metaheuristic algorithms with information feedback models, IEEE Trans. Cybern. 49 (2019), 542–555, Gu and Wang, Improving NSGA-III algorithms with information feedback models for large-scale many-objective optimization, Fut. Gen. Comput. Syst. 107 (2020), 49–69, and Zhang et al., Enhancing MOEA/D with information feedback models for large-scale many-objective optimization, Inf. Sci. 522 (2020), 1–16, new metaheuristic algorithms are introduced in terms of inserting the model F1 in SMA and other representative algorithms, namely Gravitational Search Algorithm (GSA), Charged System Search (CSS), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA). Fifth, the real-time validation of the cost-effective fuzzy controllers and their tuning approach is performed in the framework of angular position control of laboratory servo system. The comparison with other metaheuristic algorithms that solve the same optimization problem for optimal parameter tuning of cost-effective fuzzy controllers suggestively highlights the superiority of SMA. Experimental results are included.https://www.atlantis-press.com/article/125954163/viewLow-cost fuzzy controlOptimal tuningPosition controlServo systemsSlime Mould Algorithm |
| spellingShingle | Radu-Emil Precup Radu-Codrut David Raul-Cristian Roman Emil M. Petriu Alexandra-Iulia Szedlak-Stinean Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems International Journal of Computational Intelligence Systems Low-cost fuzzy control Optimal tuning Position control Servo systems Slime Mould Algorithm |
| title | Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems |
| title_full | Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems |
| title_fullStr | Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems |
| title_full_unstemmed | Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems |
| title_short | Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems |
| title_sort | slime mould algorithm based tuning of cost effective fuzzy controllers for servo systems |
| topic | Low-cost fuzzy control Optimal tuning Position control Servo systems Slime Mould Algorithm |
| url | https://www.atlantis-press.com/article/125954163/view |
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