{"title":"优化工艺流程模式参数的改进型模糊控制器","authors":"A. Antipin, E. V. Antipina, S. A. Mustafina","doi":"10.17587/mau.25.354-361","DOIUrl":null,"url":null,"abstract":"The author’s modification of a multidimensional fuzzy controller with a block for optimizing mode parameters and a block for predicting terms is considered. A block diagram of the controller, fuzzification and defuzzification schemes for continuous quantities are presented. The mechanism of operation of the logical inference block, which forms the identification number of the general composite production rule from the serial numbers of the terms of input and output variables with feedback, is described. The identification number is used as a key to retrieve information from the database about how to obtain specific numerical values of control actions, which is then transmitted to the controller defuzzification block. The general purpose of the term prediction block and the optimization block is shown. The prediction block is designed to transmit to the controller fuzzification block recommendations for a set of terms with which to begin processing the values of input variables in each scanning cycle. The optimization block is used to develop recommendations for optimizing operating parameters in accordance with specified criteria. The optimization block implements the author’s optimization algorithms, based on the use of evolutionary modeling methods and evolutionary algorithms adapted to a specific technological process. The formulation of the problem of optimal control of a dynamic process and an algorithm for its solution are presented. As an example, the problem of searching the optimal temperature regime in a batch ideal mixing reactor for the catalytic dimerization reaction of α-methylstyrene in the presence of a NaHY zeolite catalyst is considered. As a result of calculations using a genetic algorithm with real coding, where the genome is a real number, the suboptimal temperature of the refrigerant for the dimerization process of α-methylstyrene lasting 2 and 3 hours, and the corresponding concentrations of reagents, were calculated. The conducted computational experiment demonstrates the process of obtaining and issuing recommendations by a remote module for changing mode parameters and/or the system of production rules","PeriodicalId":36477,"journal":{"name":"Mekhatronika, Avtomatizatsiya, Upravlenie","volume":" 54","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modifi ed Fuzzy Controller with Optimization of Mode Parameters of Technological Process\",\"authors\":\"A. Antipin, E. V. Antipina, S. A. Mustafina\",\"doi\":\"10.17587/mau.25.354-361\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The author’s modification of a multidimensional fuzzy controller with a block for optimizing mode parameters and a block for predicting terms is considered. A block diagram of the controller, fuzzification and defuzzification schemes for continuous quantities are presented. The mechanism of operation of the logical inference block, which forms the identification number of the general composite production rule from the serial numbers of the terms of input and output variables with feedback, is described. The identification number is used as a key to retrieve information from the database about how to obtain specific numerical values of control actions, which is then transmitted to the controller defuzzification block. The general purpose of the term prediction block and the optimization block is shown. The prediction block is designed to transmit to the controller fuzzification block recommendations for a set of terms with which to begin processing the values of input variables in each scanning cycle. The optimization block is used to develop recommendations for optimizing operating parameters in accordance with specified criteria. The optimization block implements the author’s optimization algorithms, based on the use of evolutionary modeling methods and evolutionary algorithms adapted to a specific technological process. The formulation of the problem of optimal control of a dynamic process and an algorithm for its solution are presented. As an example, the problem of searching the optimal temperature regime in a batch ideal mixing reactor for the catalytic dimerization reaction of α-methylstyrene in the presence of a NaHY zeolite catalyst is considered. As a result of calculations using a genetic algorithm with real coding, where the genome is a real number, the suboptimal temperature of the refrigerant for the dimerization process of α-methylstyrene lasting 2 and 3 hours, and the corresponding concentrations of reagents, were calculated. The conducted computational experiment demonstrates the process of obtaining and issuing recommendations by a remote module for changing mode parameters and/or the system of production rules\",\"PeriodicalId\":36477,\"journal\":{\"name\":\"Mekhatronika, Avtomatizatsiya, Upravlenie\",\"volume\":\" 54\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mekhatronika, Avtomatizatsiya, Upravlenie\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17587/mau.25.354-361\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mekhatronika, Avtomatizatsiya, Upravlenie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17587/mau.25.354-361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
Modifi ed Fuzzy Controller with Optimization of Mode Parameters of Technological Process
The author’s modification of a multidimensional fuzzy controller with a block for optimizing mode parameters and a block for predicting terms is considered. A block diagram of the controller, fuzzification and defuzzification schemes for continuous quantities are presented. The mechanism of operation of the logical inference block, which forms the identification number of the general composite production rule from the serial numbers of the terms of input and output variables with feedback, is described. The identification number is used as a key to retrieve information from the database about how to obtain specific numerical values of control actions, which is then transmitted to the controller defuzzification block. The general purpose of the term prediction block and the optimization block is shown. The prediction block is designed to transmit to the controller fuzzification block recommendations for a set of terms with which to begin processing the values of input variables in each scanning cycle. The optimization block is used to develop recommendations for optimizing operating parameters in accordance with specified criteria. The optimization block implements the author’s optimization algorithms, based on the use of evolutionary modeling methods and evolutionary algorithms adapted to a specific technological process. The formulation of the problem of optimal control of a dynamic process and an algorithm for its solution are presented. As an example, the problem of searching the optimal temperature regime in a batch ideal mixing reactor for the catalytic dimerization reaction of α-methylstyrene in the presence of a NaHY zeolite catalyst is considered. As a result of calculations using a genetic algorithm with real coding, where the genome is a real number, the suboptimal temperature of the refrigerant for the dimerization process of α-methylstyrene lasting 2 and 3 hours, and the corresponding concentrations of reagents, were calculated. The conducted computational experiment demonstrates the process of obtaining and issuing recommendations by a remote module for changing mode parameters and/or the system of production rules