{"title":"一种估计工业过程混合黑盒-先验知识模型的方法","authors":"M. Stachura, K. Janiszowski","doi":"10.1109/MMAR.2011.6031307","DOIUrl":null,"url":null,"abstract":"The paper presents a combined prior knowledge - black-box approach to modeling of the dynamic systems. Proposed methodology assumes two basic steps: first an optimization of a physical model, using Particle Swarm Optimization algorithm is performed. Next, a black-box model is estimated so as to reduce the remaining error of the physical model. Proposed methodology was presented on the example of improving the accuracy of a pneumatic actuator physical model.","PeriodicalId":440376,"journal":{"name":"2011 16th International Conference on Methods & Models in Automation & Robotics","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A methodology of estimating hybrid black-box - prior knowledge models of an industrial processes\",\"authors\":\"M. Stachura, K. Janiszowski\",\"doi\":\"10.1109/MMAR.2011.6031307\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a combined prior knowledge - black-box approach to modeling of the dynamic systems. Proposed methodology assumes two basic steps: first an optimization of a physical model, using Particle Swarm Optimization algorithm is performed. Next, a black-box model is estimated so as to reduce the remaining error of the physical model. Proposed methodology was presented on the example of improving the accuracy of a pneumatic actuator physical model.\",\"PeriodicalId\":440376,\"journal\":{\"name\":\"2011 16th International Conference on Methods & Models in Automation & Robotics\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 16th International Conference on Methods & Models in Automation & Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MMAR.2011.6031307\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 16th International Conference on Methods & Models in Automation & Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2011.6031307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A methodology of estimating hybrid black-box - prior knowledge models of an industrial processes
The paper presents a combined prior knowledge - black-box approach to modeling of the dynamic systems. Proposed methodology assumes two basic steps: first an optimization of a physical model, using Particle Swarm Optimization algorithm is performed. Next, a black-box model is estimated so as to reduce the remaining error of the physical model. Proposed methodology was presented on the example of improving the accuracy of a pneumatic actuator physical model.