{"title":"快速预测逆神经控制:比较仿真与实验","authors":"K. Zmeu, B. S. Notkin, P. Dyachenko, V. Kovalev","doi":"10.1109/IJCNN.2012.6252567","DOIUrl":null,"url":null,"abstract":"There has been proposed a new approach to a neurocontrol synthesis under conditions of uncertainty. It does not directly use an optimization procedure. In terms of a synthesis technique, the proposed solution is close to inverse neurocontrol, but regarding its functions, the system has properties of a fast predictive control. There have been presented the comparison of the proposed approach with classical and modern proportional-integral-derivative (PID) systems that were obtained based on a numerical simulation and an actual control of complex plants.","PeriodicalId":287844,"journal":{"name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Fast predictive inverse neurocontrol: Comparative simulation and experiment\",\"authors\":\"K. Zmeu, B. S. Notkin, P. Dyachenko, V. Kovalev\",\"doi\":\"10.1109/IJCNN.2012.6252567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There has been proposed a new approach to a neurocontrol synthesis under conditions of uncertainty. It does not directly use an optimization procedure. In terms of a synthesis technique, the proposed solution is close to inverse neurocontrol, but regarding its functions, the system has properties of a fast predictive control. There have been presented the comparison of the proposed approach with classical and modern proportional-integral-derivative (PID) systems that were obtained based on a numerical simulation and an actual control of complex plants.\",\"PeriodicalId\":287844,\"journal\":{\"name\":\"The 2012 International Joint Conference on Neural Networks (IJCNN)\",\"volume\":\"83 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 2012 International Joint Conference on Neural Networks (IJCNN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.2012.6252567\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2012 International Joint Conference on Neural Networks (IJCNN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2012.6252567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast predictive inverse neurocontrol: Comparative simulation and experiment
There has been proposed a new approach to a neurocontrol synthesis under conditions of uncertainty. It does not directly use an optimization procedure. In terms of a synthesis technique, the proposed solution is close to inverse neurocontrol, but regarding its functions, the system has properties of a fast predictive control. There have been presented the comparison of the proposed approach with classical and modern proportional-integral-derivative (PID) systems that were obtained based on a numerical simulation and an actual control of complex plants.