{"title":"具有间歇性数据丢失的模块化系统的半自动控制","authors":"T. Tran, Q. Ha, H. Nguyen","doi":"10.1109/CASE.2011.6042449","DOIUrl":null,"url":null,"abstract":"This paper presents a control procedure of distributed stabilising agents for dynamically-coupled systems operating in the imperfect data environment of a mesh device network. A multivariable controller is applied to each single modular subsystem, which also allows for a manual control mode. To deal with the device network, intermittent data losses are compensated for on-the-fly using the incrementally accumulative quadratic constraint (AQC). The incrementally AQC is employed in the procedure of stabilising agents to accommodate the coexistence of closed-loop control and man-in-the-loop regulation. These agents render stabilising bounds for the manipulated variables in the automatic control mode, and at the same time, provide warning signals and manipulation guidance for the operators to prevent possible plant-wide destabilisation in the semi-automatic control mode. Taking the control constraints into consideration, the feasibility of AQC-based stabilising bounds is guaranteed for the consecutive datalost periods of device networks. The innovative aspect of the proposed approach rests on the stability condition developed from the input and output evolution prescribed in the controller AQC and the system dissipativity, as well as the method of remedying data losses right after the incidents. Simulation results are provided for the model predictive control of an industrial modular system in the mineral processing industry.","PeriodicalId":236208,"journal":{"name":"2011 IEEE International Conference on Automation Science and Engineering","volume":"73 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Semi-automatic control of modular systems with intermittent data losses\",\"authors\":\"T. Tran, Q. Ha, H. Nguyen\",\"doi\":\"10.1109/CASE.2011.6042449\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a control procedure of distributed stabilising agents for dynamically-coupled systems operating in the imperfect data environment of a mesh device network. A multivariable controller is applied to each single modular subsystem, which also allows for a manual control mode. To deal with the device network, intermittent data losses are compensated for on-the-fly using the incrementally accumulative quadratic constraint (AQC). The incrementally AQC is employed in the procedure of stabilising agents to accommodate the coexistence of closed-loop control and man-in-the-loop regulation. These agents render stabilising bounds for the manipulated variables in the automatic control mode, and at the same time, provide warning signals and manipulation guidance for the operators to prevent possible plant-wide destabilisation in the semi-automatic control mode. Taking the control constraints into consideration, the feasibility of AQC-based stabilising bounds is guaranteed for the consecutive datalost periods of device networks. The innovative aspect of the proposed approach rests on the stability condition developed from the input and output evolution prescribed in the controller AQC and the system dissipativity, as well as the method of remedying data losses right after the incidents. Simulation results are provided for the model predictive control of an industrial modular system in the mineral processing industry.\",\"PeriodicalId\":236208,\"journal\":{\"name\":\"2011 IEEE International Conference on Automation Science and Engineering\",\"volume\":\"73 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Automation Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CASE.2011.6042449\",\"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 IEEE International Conference on Automation Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASE.2011.6042449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Semi-automatic control of modular systems with intermittent data losses
This paper presents a control procedure of distributed stabilising agents for dynamically-coupled systems operating in the imperfect data environment of a mesh device network. A multivariable controller is applied to each single modular subsystem, which also allows for a manual control mode. To deal with the device network, intermittent data losses are compensated for on-the-fly using the incrementally accumulative quadratic constraint (AQC). The incrementally AQC is employed in the procedure of stabilising agents to accommodate the coexistence of closed-loop control and man-in-the-loop regulation. These agents render stabilising bounds for the manipulated variables in the automatic control mode, and at the same time, provide warning signals and manipulation guidance for the operators to prevent possible plant-wide destabilisation in the semi-automatic control mode. Taking the control constraints into consideration, the feasibility of AQC-based stabilising bounds is guaranteed for the consecutive datalost periods of device networks. The innovative aspect of the proposed approach rests on the stability condition developed from the input and output evolution prescribed in the controller AQC and the system dissipativity, as well as the method of remedying data losses right after the incidents. Simulation results are provided for the model predictive control of an industrial modular system in the mineral processing industry.