{"title":"基于增益自适应Smith预测器的不同采样率双环网络控制系统设计","authors":"Hong Zhao, Ke Che","doi":"10.1145/3305275.3305333","DOIUrl":null,"url":null,"abstract":"A class of dual loop networked control systems with different sampling rate is discussed in this paper. Generally, Smith predictor can be used to overcome the influence of network delay. However, influence of prediction model inaccuracy, different sampling rate and interference always appear in the actual systems, and the systems based on conventional Smith predictor cannot achieve the desired control effect. The gain adaptive Smith predictor is proposed for this class of networked control systems, which can be used to overcome the problems caused by inaccurate prediction model, interference and various sampling rate. The simulation results based on MATLAB show that the proposed method is efficient and feasible.","PeriodicalId":370976,"journal":{"name":"Proceedings of the International Symposium on Big Data and Artificial Intelligence","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design of Dual Loop Networked Control Systems with Different Sampling Rate Based on Gain Adaptive Smith Predictor\",\"authors\":\"Hong Zhao, Ke Che\",\"doi\":\"10.1145/3305275.3305333\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A class of dual loop networked control systems with different sampling rate is discussed in this paper. Generally, Smith predictor can be used to overcome the influence of network delay. However, influence of prediction model inaccuracy, different sampling rate and interference always appear in the actual systems, and the systems based on conventional Smith predictor cannot achieve the desired control effect. The gain adaptive Smith predictor is proposed for this class of networked control systems, which can be used to overcome the problems caused by inaccurate prediction model, interference and various sampling rate. The simulation results based on MATLAB show that the proposed method is efficient and feasible.\",\"PeriodicalId\":370976,\"journal\":{\"name\":\"Proceedings of the International Symposium on Big Data and Artificial Intelligence\",\"volume\":\"102 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Symposium on Big Data and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3305275.3305333\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Symposium on Big Data and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3305275.3305333","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of Dual Loop Networked Control Systems with Different Sampling Rate Based on Gain Adaptive Smith Predictor
A class of dual loop networked control systems with different sampling rate is discussed in this paper. Generally, Smith predictor can be used to overcome the influence of network delay. However, influence of prediction model inaccuracy, different sampling rate and interference always appear in the actual systems, and the systems based on conventional Smith predictor cannot achieve the desired control effect. The gain adaptive Smith predictor is proposed for this class of networked control systems, which can be used to overcome the problems caused by inaccurate prediction model, interference and various sampling rate. The simulation results based on MATLAB show that the proposed method is efficient and feasible.