{"title":"Fuzzy models based economic predictive control for a combined cycle power plant boiler","authors":"D. Śaez, A. Cipriano","doi":"10.1109/ISIC.1999.796691","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796691","url":null,"abstract":"A boiler simulator for a combined cycle power plant, based on phenomenological equations and developed in Matlab-SIMULINK, is presented. Then, a new fuzzy control strategy based on minimizing the operational costs of a boiler is designed and implemented. The optimization problem is solved using dynamic fuzzy models and predictive control theory.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117336418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Causal modeling for supervision","authors":"J. Montmain, S. Gentil","doi":"10.1109/ISIC.1999.796660","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796660","url":null,"abstract":"Today, process control and monitoring are evolving to include plant safety and availability management, online diagnosis and maintenance policy. Human operators are at the highest hierarchical level in the organization of the control system. Supervision aims are to assist control operators in their decision-making tasks, to help them understand and identify operating situations underway in a man-machine cooperation objective. The paper demonstrates how developments in causal reasoning can contribute judiciously to the supervision problem. An original causal modeling that includes time management is described and used for simulation, explanation and diagnosis.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"289 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122783548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An artificial neural network for optimizing safety and quality in thermal food processing","authors":"D. Kseibat, O. Basir, G. Mittal","doi":"10.1109/ISIC.1999.796687","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796687","url":null,"abstract":"Presents a backpropagation artificial neural network for optimizing food safety and quality in thermal processing applications. Five inputs (can size, initial temperature, thermal diffusivity, sensitivity indicator of microorganism, and sensitivity indicator of quality) are used as inputs to the network. The network computes the optimal control parameters (sterilization temperature, process time) and quality degradation of the food. This study is based on a wide range of microorganisms involved in foods.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124007962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A behavior based controller architecture and the transition to an industry application","authors":"M. Roeckel, R. Rivoir, R. E. Gibson","doi":"10.1109/ISIC.1999.796675","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796675","url":null,"abstract":"While technology transfer has been in the spotlight of late, it is rare to find the necessary combination of a sufficiently mature technology, interested developers, and a commercial need. Even with the above combination, a good plan of action is needed to efficiently effect the transfer. This paper describes a successful technology transfer of the prototype intelligent controller (PIC) architecture from the Applied Research Laboratory (ARL) of the Pennsylvania State University to the Northrop Grumman Corporation/Oceanic and Naval Systems Division and ARL's role in the development of the Autonomous Sortie Controller (ASC), a behavior based controller for an autonomous underwater vehicle application. This controller was designed, developed, tested, and successfully demonstrated in-water in a 13 month period between March 1998 and April 1999.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"921 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116415372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Intelligent control and anesthesiology: enhancing physician decision making","authors":"J. Shelton, W. B. Murray","doi":"10.1109/ISIC.1999.796677","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796677","url":null,"abstract":"The advantages of using an intelligent controller to enhance physician decision-making within an operating theatre environment is investigated. In particular, ways in which incorporating an intelligent controller as an integral part of an anesthesiologist/patient loop are considered. The intelligent controller can provide a physician with information derived by fusing data gathered by independent operating room monitors, information that is not currently available or readily derivable and which might offer additional particulars useful in diagnosis and treatment. The intelligent controller is also viewed as potentially providing control of operating room effecters via merged data, thereby helping to reduce potential task and information overload.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133610334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A genetic based control structure for active control","authors":"K. Yim, Jong Boo Kim, T. Lee","doi":"10.1109/ISIC.1999.796685","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796685","url":null,"abstract":"Presents a genetic based control structure for active control. The proposed active control structure has an adaptive system whose controller is an infinite impulse response (IIR) filter and the adaptive mechanism is a genetic algorithm. Adaptive filtering schemes based on a genetic algorithm have been studied, but their application is limited to the system that is able to know desired signals directly. In general active noise and vibration control systems are not able to sense desired signals directly, so they have some difficulties or problems in that the learning sample set is proportional to the population size. The proposed active controller is composed of genetic controllers that can be learned by one sample set per one generation. Also this structure can be properly applied to an active control system. Computer simulation shows that proposed genetic structured IIR active controller gives a good result for feedforward active noise control systems.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122201149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fuzzy model predictive control: techniques, stability issues, and examples","authors":"H. Nounou, Kevin M. Passino","doi":"10.1109/ISIC.1999.796692","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796692","url":null,"abstract":"Fuzzy model predictive control (FMPC) algorithms presented here are model-based control schemes in which the models used for prediction are Takagi-Sugeno fuzzy systems (TSFS). Three approaches to FMPC design are discussed. The fuzzy model in the first approach can be represented as a time-varying affine model that is used for control. In the second approach, the fuzzy system is a convex combination of multiple affine models, where the control is a convex combination of multiple controllers. Lastly, the control of the third algorithm is obtained when only the model with the highest certainty is used in the design. Also, we extend the idea to have an adaptive controller for the first algorithm, where the parameters of the fuzzy model are updated online.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116913620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the supervisory synthesis for distributed control of discrete event dynamic systems with communication delays","authors":"M. Yeddes, H. Alla, R. David","doi":"10.1109/ISIC.1999.796620","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796620","url":null,"abstract":"The supervisory control theory, first introduced by Ramadge and Wonham (1987), is based on an automata concept. The aim of this theory is to synthesize a supervisor in order to respect some logic specifications. Control systems, however, are often distributed, for quite obvious reasons of performance, fault tolerance, and distribution of sensors and actuators to different physical locations. Thus, an extension of Ramadge and Wonham theory to decentralized supervisory control is used. In this case, when data transmission between different sites takes a non null time, the case study is more crucial. Therefore, it proves that it is difficult, if not impossible, to know by common sense whether global functioning is correct in order to respect the specifications. In the paper, supervisor synthesis is based not only on the controllable events but also by introducing and determining time periods in control models. The role of these time periods is to absorb communication delays in such a way that these delays do not affect the role of the supervisor in respecting the specifications.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134454605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Interpolation behavior of TS fuzzy controllers","authors":"M. Alata, K. Demirli, A. Bulgak","doi":"10.1109/ISIC.1999.796681","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796681","url":null,"abstract":"In this paper the influence of the shape, the distribution of the membership functions and the order of the functional consequent (in case of Takagi-Sugeno controller, 1985) on the interpolation function of the fuzzy system is investigated. A linear membership function, product conjunction operator, and a general functional consequent are used. Different interpolation behavior can be observed by changing the conjunction operator to minimum, or the membership function to Gaussian.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"59 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133037688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A behavior-based architecture for the design of intelligent controllers for autonomous systems","authors":"J. Stover, R. Kumar","doi":"10.1109/ISIC.1999.796673","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796673","url":null,"abstract":"Describes a behavior-based intelligent control architecture for designing controllers which, based on their observation of sensor signals compute the discrete control actions. The behavior-based approach yields an intelligent controller which is a cascade of a perceptor, and a responder. The perceptor builds internal representations as object class instances of the external world as detected by the sensors. The existence of class instances with certain properties enables the responder to react to them by executing appropriate behaviors. The responder is a discrete event system that computes the discrete control actions by executing one of the enabled behaviors. The behavioral approach additionally yields a hierarchical two layered responder, thus facilitating a better management of complexity. The responder uses the perceptor inputs to first compute the higher level activities, called behaviors, and next the corresponding lower level activities, called actions.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"49 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133911669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}