A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System
In this work, we propose a real proportional-integral-derivative plus second-order derivative (PIDD2) controller as an efficient controller for vehicle cruise control systems to address the challenging issues related to efficient operation. In this regard, this paper is the first report in the liter...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2023
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://depot.sorbonne.ae/handle/20.500.12458/1386 |
| الوسوم: |
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| _version_ | 1857415062283616257 |
|---|---|
| author | Ekinci, Serdar |
| author2 | Izci, Davut Abualigah, Laith Abu Zitar, Raed |
| author2_role | author author author |
| author_facet | Ekinci, Serdar Izci, Davut Abualigah, Laith Abu Zitar, Raed |
| author_role | author |
| dc.creator.none.fl_str_mv | Ekinci, Serdar Izci, Davut Abualigah, Laith Abu Zitar, Raed |
| dc.date.none.fl_str_mv | 2023-02-13T04:51:53Z 2023-02-13T04:51:53Z 2023 |
| dc.identifier.none.fl_str_mv | 1672-6529 2543-2141 https://depot.sorbonne.ae/handle/20.500.12458/1386 10.1007/s42235-023-00336-y |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Journal of Bionic Engineering |
| dc.subject.none.fl_str_mv | Aquila optimizer Chaotic local search Modified opposition-based learning Real PIDD2 controller Vehicle cruise control system Bionic engineering |
| dc.title.none.fl_str_mv | A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System |
| dc.type.none.fl_str_mv | Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal article |
| description | In this work, we propose a real proportional-integral-derivative plus second-order derivative (PIDD2) controller as an efficient controller for vehicle cruise control systems to address the challenging issues related to efficient operation. In this regard, this paper is the first report in the literature demonstrating the implementation of a real PIDD2 controller for controlling the respective system. We construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning mechanism. We also propose a simple yet effective objective function to increase the performance of the proposed algorithm (CmOBL-AO) to adjust the real PIDD2 controller's parameters effectively. We show the CmOBL-AO algorithm to perform better than the differential evolution algorithm, gravitational search algorithm, African vultures optimization, and the Aquila Optimizer using well-known unimodal, multimodal benchmark functions. CEC2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO algorithm. For the vehicle cruise control system, we confirm the more excellent performance of the proposed method against particle swarm, gray wolf, salp swarm, and original Aquila optimizers using statistical, Wilcoxon signed-rank, time response, robustness, and disturbance rejection analyses. We also use fourteen reported methods in the literature for the vehicle cruise control system to further verify the more promising performance of the CmOBL-AO-based real PIDD2 controller from a wider perspective. The excellent performance of the proposed method is also illustrated through different quality indicators and different operating speeds. Lastly, we also demonstrate the good performing capability of the CmOBL-AO algorithm for real traffic cases. We show the CmOBL-AO-based real PIDD2 controller as the most efficient method to control a vehicle cruise control system. |
| id | sorbonner_a484ffce83d4eb910abf88df2b0061b7 |
| identifier_str_mv | 1672-6529 2543-2141 10.1007/s42235-023-00336-y |
| language_invalid_str_mv | en |
| network_acronym_str | sorbonner |
| network_name_str | Sorbonne University Abu Dhabi repository |
| oai_identifier_str | oai:depot.sorbonne.ae:20.500.12458/1386 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control SystemEkinci, SerdarIzci, DavutAbualigah, LaithAbu Zitar, RaedAquila optimizerChaotic local searchModified opposition-based learningReal PIDD2 controllerVehicle cruise control systemBionic engineeringIn this work, we propose a real proportional-integral-derivative plus second-order derivative (PIDD2) controller as an efficient controller for vehicle cruise control systems to address the challenging issues related to efficient operation. In this regard, this paper is the first report in the literature demonstrating the implementation of a real PIDD2 controller for controlling the respective system. We construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning mechanism. We also propose a simple yet effective objective function to increase the performance of the proposed algorithm (CmOBL-AO) to adjust the real PIDD2 controller's parameters effectively. We show the CmOBL-AO algorithm to perform better than the differential evolution algorithm, gravitational search algorithm, African vultures optimization, and the Aquila Optimizer using well-known unimodal, multimodal benchmark functions. CEC2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO algorithm. For the vehicle cruise control system, we confirm the more excellent performance of the proposed method against particle swarm, gray wolf, salp swarm, and original Aquila optimizers using statistical, Wilcoxon signed-rank, time response, robustness, and disturbance rejection analyses. We also use fourteen reported methods in the literature for the vehicle cruise control system to further verify the more promising performance of the CmOBL-AO-based real PIDD2 controller from a wider perspective. The excellent performance of the proposed method is also illustrated through different quality indicators and different operating speeds. Lastly, we also demonstrate the good performing capability of the CmOBL-AO algorithm for real traffic cases. We show the CmOBL-AO-based real PIDD2 controller as the most efficient method to control a vehicle cruise control system.2023-02-13T04:51:53Z2023-02-13T04:51:53Z2023Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal article1672-65292543-2141https://depot.sorbonne.ae/handle/20.500.12458/138610.1007/s42235-023-00336-yenJournal of Bionic Engineeringoai:depot.sorbonne.ae:20.500.12458/13862023-06-14T09:44:24Z |
| spellingShingle | A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System Ekinci, Serdar Aquila optimizer Chaotic local search Modified opposition-based learning Real PIDD2 controller Vehicle cruise control system Bionic engineering |
| title | A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System |
| title_full | A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System |
| title_fullStr | A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System |
| title_full_unstemmed | A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System |
| title_short | A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System |
| title_sort | A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System |
| topic | Aquila optimizer Chaotic local search Modified opposition-based learning Real PIDD2 controller Vehicle cruise control system Bionic engineering |
| url | https://depot.sorbonne.ae/handle/20.500.12458/1386 |