{"title":"基于元启发式算法的非负型DC-DC变换器自适应控制器设计","authors":"M. Moses, S. Rajarajacholan","doi":"10.1166/jmihi.2022.3929","DOIUrl":null,"url":null,"abstract":"Purpose: Meta-heuristic (MH) methods are used to develop an adaptive sliding mode controller for a POEL converter. MH algorithms have been used to address a variety of engineering optimization problems. Which will use for Bio medical hybrid systems applications. Design/Methodology:\n Particle Swarm Optimization (PSO) approach is well known and it could expedite the convergence characteristic in numerous applications. By means of amending PSO parameters like, inertia mass, social and perceptive agents at every generation, Modern Parameter Improved Particle Swarm Optimization\n (MPIPSO) algorithm which is a more enhanced version of PSO is developed. Findings: Since the converter output voltage’s integral squared error (ISE) has been chosen as a neutral function, the optimal PI controller design may be expressed in terms of optimization problems. Originality/Value:\n The superiority of the proposed MPIPSO based sliding mode controller has been shown by comparing the results with other existing MH optimization methodologies.","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"197 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Modified Adaptive Controller Design for Non Negative DC-DC Converter Using Meta-Heuristic Algorithms for Bio Medical Hybrid Application\",\"authors\":\"M. Moses, S. Rajarajacholan\",\"doi\":\"10.1166/jmihi.2022.3929\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose: Meta-heuristic (MH) methods are used to develop an adaptive sliding mode controller for a POEL converter. MH algorithms have been used to address a variety of engineering optimization problems. Which will use for Bio medical hybrid systems applications. Design/Methodology:\\n Particle Swarm Optimization (PSO) approach is well known and it could expedite the convergence characteristic in numerous applications. By means of amending PSO parameters like, inertia mass, social and perceptive agents at every generation, Modern Parameter Improved Particle Swarm Optimization\\n (MPIPSO) algorithm which is a more enhanced version of PSO is developed. Findings: Since the converter output voltage’s integral squared error (ISE) has been chosen as a neutral function, the optimal PI controller design may be expressed in terms of optimization problems. Originality/Value:\\n The superiority of the proposed MPIPSO based sliding mode controller has been shown by comparing the results with other existing MH optimization methodologies.\",\"PeriodicalId\":393031,\"journal\":{\"name\":\"J. Medical Imaging Health Informatics\",\"volume\":\"197 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"J. Medical Imaging Health Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1166/jmihi.2022.3929\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Medical Imaging Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1166/jmihi.2022.3929","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Modified Adaptive Controller Design for Non Negative DC-DC Converter Using Meta-Heuristic Algorithms for Bio Medical Hybrid Application
Purpose: Meta-heuristic (MH) methods are used to develop an adaptive sliding mode controller for a POEL converter. MH algorithms have been used to address a variety of engineering optimization problems. Which will use for Bio medical hybrid systems applications. Design/Methodology:
Particle Swarm Optimization (PSO) approach is well known and it could expedite the convergence characteristic in numerous applications. By means of amending PSO parameters like, inertia mass, social and perceptive agents at every generation, Modern Parameter Improved Particle Swarm Optimization
(MPIPSO) algorithm which is a more enhanced version of PSO is developed. Findings: Since the converter output voltage’s integral squared error (ISE) has been chosen as a neutral function, the optimal PI controller design may be expressed in terms of optimization problems. Originality/Value:
The superiority of the proposed MPIPSO based sliding mode controller has been shown by comparing the results with other existing MH optimization methodologies.