Optimization of basic PID control algorithm based on genetic algorithm and Matlab Article Swipe
This paper investigates how to optimize the basic PID algorithm by using population genetic forms. "In traditional PID control, the tuning of PID parameters mostly relies on the experience of the tuner. The main purpose of this paper is to use an algorithm that can automatically tune its parameters to self-tune a PID controller for an actual model." Based on the principle of genetic algorithm, this paper compares the traditional PID controller tuning methods to study the trend of the PID parameters during the iteration process as well as the trend of the PID controller adaptability. Through the principle of the algorithm and the iterative output, as well as in the code set the weights occupied by different performance indicators, it can not only flexibly adjust the degree of adaptation and make the algorithm more flexible, but also prove that the use of genetic algorithms for the rectification of the PID is more adaptable and convenient, with promising research prospects
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.54254/2753-8818/30/20241103
- https://www.ewadirect.com/proceedings/tns/article/view/9786/pdf
- OA Status
- hybrid
- Cited By
- 1
- References
- 5
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391142704
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391142704Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.54254/2753-8818/30/20241103Digital Object Identifier
- Title
-
Optimization of basic PID control algorithm based on genetic algorithm and MatlabWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-23Full publication date if available
- Authors
-
Yingjie MaList of authors in order
- Landing page
-
https://doi.org/10.54254/2753-8818/30/20241103Publisher landing page
- PDF URL
-
https://www.ewadirect.com/proceedings/tns/article/view/9786/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://www.ewadirect.com/proceedings/tns/article/view/9786/pdfDirect OA link when available
- Concepts
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PID controller, Genetic algorithm, Algorithm, Computer science, Control theory (sociology), MATLAB, Set (abstract data type), Adaptability, Process (computing), Population, Control engineering, Control (management), Engineering, Temperature control, Artificial intelligence, Machine learning, Ecology, Demography, Operating system, Biology, Sociology, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1Per-year citation counts (last 5 years)
- References (count)
-
5Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.algorithm | 9, 42, 101, 133 |
| abstract_inverted_index.different | 117 |
| abstract_inverted_index.flexible, | 135 |
| abstract_inverted_index.iteration | 84 |
| abstract_inverted_index.iterative | 104 |
| abstract_inverted_index.principle | 61, 98 |
| abstract_inverted_index.promising | 157 |
| abstract_inverted_index.prospects | 159 |
| abstract_inverted_index.self-tune | 50 |
| abstract_inverted_index.adaptation | 129 |
| abstract_inverted_index.algorithm, | 64 |
| abstract_inverted_index.algorithms | 144 |
| abstract_inverted_index.controller | 53, 71, 94 |
| abstract_inverted_index.experience | 28 |
| abstract_inverted_index.parameters | 23, 48, 81 |
| abstract_inverted_index.population | 12 |
| abstract_inverted_index.convenient, | 155 |
| abstract_inverted_index.indicators, | 119 |
| abstract_inverted_index.performance | 118 |
| abstract_inverted_index.traditional | 16, 69 |
| abstract_inverted_index.investigates | 2 |
| abstract_inverted_index.adaptability. | 95 |
| abstract_inverted_index.automatically | 45 |
| abstract_inverted_index.rectification | 147 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5101695154 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 1 |
| corresponding_institution_ids | https://openalex.org/I113940042, https://openalex.org/I118692353, https://openalex.org/I148128674 |
| citation_normalized_percentile.value | 0.56751456 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |