Design and Development of an Optimal Control Model in System Dynamics through State-Space Representation
Control engineering and state-space representation are valuable tools in the analysis and design of dynamic systems. In this research, a methodology is proposed that uses these approaches to transform a system-dynamics simulation model into a mathematical model. This is achieved by expressing input,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/12/7154 |
| _version_ | 1797596258310815744 |
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| author | Jorge Manuel Barrios Sánchez Roberto Baeza Serrato |
| author_facet | Jorge Manuel Barrios Sánchez Roberto Baeza Serrato |
| author_sort | Jorge Manuel Barrios Sánchez |
| collection | DOAJ |
| description | Control engineering and state-space representation are valuable tools in the analysis and design of dynamic systems. In this research, a methodology is proposed that uses these approaches to transform a system-dynamics simulation model into a mathematical model. This is achieved by expressing input, output and state variables as input, output and state vectors, respectively, allowing the representation of the model in matrix form. The resulting model is linear and time-invariant, facilitating its analysis and design. Through the use of this methodology, the system transfer matrix is obtained, which allows the analysis and design of the optimal control of the simulation model. The Ackermann gain-control technique is used to determine the optimal control of the system, which results in a shorter settlement time. This research proposal seeks to mathematically strengthen simulation models and provide an analytical alternative through modern control engineering in SD simulation models. This would allow more informed and effective decisions in the implementation of dynamic systems. |
| first_indexed | 2024-03-11T02:49:01Z |
| format | Article |
| id | doaj.art-af4548e2167e4111acb3e85018a0ec68 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T02:49:01Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-af4548e2167e4111acb3e85018a0ec682023-11-18T09:09:53ZengMDPI AGApplied Sciences2076-34172023-06-011312715410.3390/app13127154Design and Development of an Optimal Control Model in System Dynamics through State-Space RepresentationJorge Manuel Barrios Sánchez0Roberto Baeza Serrato1Department of Multidisciplinary Studies, Engineering Division, Campus Irapuato-Salamanca, University of Guanajuato, Yuriria, Guanajuato 38940, MexicoDepartment of Multidisciplinary Studies, Engineering Division, Campus Irapuato-Salamanca, University of Guanajuato, Yuriria, Guanajuato 38940, MexicoControl engineering and state-space representation are valuable tools in the analysis and design of dynamic systems. In this research, a methodology is proposed that uses these approaches to transform a system-dynamics simulation model into a mathematical model. This is achieved by expressing input, output and state variables as input, output and state vectors, respectively, allowing the representation of the model in matrix form. The resulting model is linear and time-invariant, facilitating its analysis and design. Through the use of this methodology, the system transfer matrix is obtained, which allows the analysis and design of the optimal control of the simulation model. The Ackermann gain-control technique is used to determine the optimal control of the system, which results in a shorter settlement time. This research proposal seeks to mathematically strengthen simulation models and provide an analytical alternative through modern control engineering in SD simulation models. This would allow more informed and effective decisions in the implementation of dynamic systems.https://www.mdpi.com/2076-3417/13/12/7154system dynamicForresterAckermanndifferential equationstransfer matrixoptimal |
| spellingShingle | Jorge Manuel Barrios Sánchez Roberto Baeza Serrato Design and Development of an Optimal Control Model in System Dynamics through State-Space Representation Applied Sciences system dynamic Forrester Ackermann differential equations transfer matrix optimal |
| title | Design and Development of an Optimal Control Model in System Dynamics through State-Space Representation |
| title_full | Design and Development of an Optimal Control Model in System Dynamics through State-Space Representation |
| title_fullStr | Design and Development of an Optimal Control Model in System Dynamics through State-Space Representation |
| title_full_unstemmed | Design and Development of an Optimal Control Model in System Dynamics through State-Space Representation |
| title_short | Design and Development of an Optimal Control Model in System Dynamics through State-Space Representation |
| title_sort | design and development of an optimal control model in system dynamics through state space representation |
| topic | system dynamic Forrester Ackermann differential equations transfer matrix optimal |
| url | https://www.mdpi.com/2076-3417/13/12/7154 |
| work_keys_str_mv | AT jorgemanuelbarriossanchez designanddevelopmentofanoptimalcontrolmodelinsystemdynamicsthroughstatespacerepresentation AT robertobaezaserrato designanddevelopmentofanoptimalcontrolmodelinsystemdynamicsthroughstatespacerepresentation |