{"title":"PID、模糊和模型预测控制在实际非线性装置中的应用","authors":"K. Borgeest, P. Schneider","doi":"10.4018/IJRAT.2016010102","DOIUrl":null,"url":null,"abstract":"For the cooling system of a mobile machine with m control variables and with n≤m correction variables different control strategies have been investigated in order to minimize power to save energy and to reduce fan noise with sufficient cooling. The plant is nonlinear and not identified. Three different kinds of controllers have been investigated in several variations, i.e. fuzzy control, PI(D) and model predictive control (MPC). 14 different criteria have been used for evaluation. In many respects a linear controller with fuzzy prediction proved best, in particular the prediction model can handle nonlinear properties of the plant. A problem of advanced control schemes with unidentified plants is the difficulty to prove stability. KeywoRDS Construction Machine, Defuzzification, Fan Control, Fan Noise, Feedforward, Fuzzy Control, Fuzzification, Mamdani, Model Predictive Control, MPC, Nonlinear System, PI Control, PID Control","PeriodicalId":249760,"journal":{"name":"Int. J. Robotics Appl. Technol.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PID, Fuzzy and Model Predictive Control Applied to a Practical Nonlinear Plant\",\"authors\":\"K. Borgeest, P. Schneider\",\"doi\":\"10.4018/IJRAT.2016010102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the cooling system of a mobile machine with m control variables and with n≤m correction variables different control strategies have been investigated in order to minimize power to save energy and to reduce fan noise with sufficient cooling. The plant is nonlinear and not identified. Three different kinds of controllers have been investigated in several variations, i.e. fuzzy control, PI(D) and model predictive control (MPC). 14 different criteria have been used for evaluation. In many respects a linear controller with fuzzy prediction proved best, in particular the prediction model can handle nonlinear properties of the plant. A problem of advanced control schemes with unidentified plants is the difficulty to prove stability. KeywoRDS Construction Machine, Defuzzification, Fan Control, Fan Noise, Feedforward, Fuzzy Control, Fuzzification, Mamdani, Model Predictive Control, MPC, Nonlinear System, PI Control, PID Control\",\"PeriodicalId\":249760,\"journal\":{\"name\":\"Int. J. Robotics Appl. Technol.\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Robotics Appl. Technol.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJRAT.2016010102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Robotics Appl. Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJRAT.2016010102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PID, Fuzzy and Model Predictive Control Applied to a Practical Nonlinear Plant
For the cooling system of a mobile machine with m control variables and with n≤m correction variables different control strategies have been investigated in order to minimize power to save energy and to reduce fan noise with sufficient cooling. The plant is nonlinear and not identified. Three different kinds of controllers have been investigated in several variations, i.e. fuzzy control, PI(D) and model predictive control (MPC). 14 different criteria have been used for evaluation. In many respects a linear controller with fuzzy prediction proved best, in particular the prediction model can handle nonlinear properties of the plant. A problem of advanced control schemes with unidentified plants is the difficulty to prove stability. KeywoRDS Construction Machine, Defuzzification, Fan Control, Fan Noise, Feedforward, Fuzzy Control, Fuzzification, Mamdani, Model Predictive Control, MPC, Nonlinear System, PI Control, PID Control