Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms
Recent advancements in computer science include some optimization models that have been developed and used in real applications. Some metaheuristic search/optimization algorithms have been tested to obtain optimal solutions to speed controller applications in self-driving cars. Some metaheuristic al...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/5538296 |
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| _version_ | 1832566338683404288 |
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| author | Luis Fernando de Mingo López Francisco Serradilla García José Eugenio Naranjo Hernández Nuria Gómez Blas |
| author_facet | Luis Fernando de Mingo López Francisco Serradilla García José Eugenio Naranjo Hernández Nuria Gómez Blas |
| author_sort | Luis Fernando de Mingo López |
| collection | DOAJ |
| description | Recent advancements in computer science include some optimization models that have been developed and used in real applications. Some metaheuristic search/optimization algorithms have been tested to obtain optimal solutions to speed controller applications in self-driving cars. Some metaheuristic algorithms are based on social behaviour, resulting in several search models, functions, and parameters, and thus algorithm-specific strengths and weaknesses. The present paper proposes a fitness function on the basis of the mathematical description of proportional integrative derivate controllers showing that mean square error is not always the best measure when looking for a solution to the problem. The fitness developed in this paper contains features and equations from the mathematical background of proportional integrative derivative controllers to calculate the best performance of the system. Such results are applied to quantitatively evaluate the performance of twenty-one optimization algorithms. Furthermore, improved versions of the fitness function are considered, in order to investigate which aspects are enhanced by applying the optimization algorithms. Results show that the right fitness function is a key point to get a good performance, regardless of the chosen algorithm. The aim of this paper is to present a novel objective function to carry out optimizations of the gains of a PID controller, using several computational intelligence techniques to perform the optimizations. The result of these optimizations will demonstrate the improved efficiency of the selected control schema. |
| format | Article |
| id | doaj-art-6190b40c49e244d5b3349fb0a7ebd004 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-6190b40c49e244d5b3349fb0a7ebd0042025-02-03T01:04:26ZengWileyJournal of Advanced Transportation2042-31952021-01-01202110.1155/2021/5538296Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic AlgorithmsLuis Fernando de Mingo López0Francisco Serradilla García1José Eugenio Naranjo Hernández2Nuria Gómez Blas3ETSI de Sistemas InformáticosETSI de Sistemas InformáticosETSI de Sistemas InformáticosETSI de Sistemas InformáticosRecent advancements in computer science include some optimization models that have been developed and used in real applications. Some metaheuristic search/optimization algorithms have been tested to obtain optimal solutions to speed controller applications in self-driving cars. Some metaheuristic algorithms are based on social behaviour, resulting in several search models, functions, and parameters, and thus algorithm-specific strengths and weaknesses. The present paper proposes a fitness function on the basis of the mathematical description of proportional integrative derivate controllers showing that mean square error is not always the best measure when looking for a solution to the problem. The fitness developed in this paper contains features and equations from the mathematical background of proportional integrative derivative controllers to calculate the best performance of the system. Such results are applied to quantitatively evaluate the performance of twenty-one optimization algorithms. Furthermore, improved versions of the fitness function are considered, in order to investigate which aspects are enhanced by applying the optimization algorithms. Results show that the right fitness function is a key point to get a good performance, regardless of the chosen algorithm. The aim of this paper is to present a novel objective function to carry out optimizations of the gains of a PID controller, using several computational intelligence techniques to perform the optimizations. The result of these optimizations will demonstrate the improved efficiency of the selected control schema.http://dx.doi.org/10.1155/2021/5538296 |
| spellingShingle | Luis Fernando de Mingo López Francisco Serradilla García José Eugenio Naranjo Hernández Nuria Gómez Blas Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms Journal of Advanced Transportation |
| title | Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms |
| title_full | Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms |
| title_fullStr | Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms |
| title_full_unstemmed | Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms |
| title_short | Speed Proportional Integrative Derivative Controller: Optimization Functions in Metaheuristic Algorithms |
| title_sort | speed proportional integrative derivative controller optimization functions in metaheuristic algorithms |
| url | http://dx.doi.org/10.1155/2021/5538296 |
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