Intelligent Control Systems Research Laboratory

Activity of the research laboratory
The research laboratory deals with with interdisciplinary problems of systems- and control theory, computer science, and artificial intelligence, in particular. The following research directions are followed.
 
  1. Intelligent diagnostics of complex dynamic systems
    Diagnostics of complex large-sized industrial systems can be performed based on more than one complementary but heterogeneous information sources. Moreover, the algorithms are of high complexity because of the large size, the complexity and the heuristic nature of the diagnostic information. Because of the above features, model based intelligent methods and discrete event systems (e.g. Petri nets) based methods are used for the diagnostics of complex industrial systems.
    Actual research projects include the development of diagnostic methods based on the analysis of the reachability graph of the colored Petri net model of a complex dynamic system. Furthermore, prediction-base diagnostic algorithms are also researched for electrical networks that apply the colored Petri net model of the system.
  1. Modeling, analysis and control of nonlinear dynamic systems with applications in (electrical) energetics
    The state- and parameter estimation of nonlinear and stochastic systems is an intensively researched area which has several practical benefits exceeding its theoretical difficulties and beauty. The aim of the research is to develop methods and algorithms for optimal operation and optimal network integration of devices (generators, accumulators, solar panels etc.) found in renewable energy systems using the tools of modern nonlinear systems and control theory.
    Actual research projects include the energy-optimal scheduling of household and industrial freezers, the energy-optimal operation and aging prediction of energy storage devices (accumulators), and energy-optimal operation of solar panels.
  1. Analysis, identification and control of complex nonlinear positive systems
    An important class of complex nonlinear positive systems, the class of polynomial systems that correspond to chemical reaction networks are investigated. Convex optimization based methods are developed for this class for stability analysis and for design of stabilizing feedback controllers.
    Another mportant class, the class of quasi-polynomial systems is also in the focus of the research. Egy másik fontos pozitív rendszerosztállyal, a kvázipolinom rendszerekkel is foglalkoznak. Convex optimization based methods are developed for this class, too, for stability analysis and for design of stabilizing feedback controllers.
Introduction of the head of the laboratory
hangos katalinKatalin Hangos has an M.Sc. degree in Chemistry (ELTE TTK, 1976), M.Sc. in Computer Science (ELTE TTK, 1980), Academic Doctor of the Hungarian Academy of Science (MTA) (1993), habilitated doctor (process systems engineering, 1994, information technology, 2000). At present she is a university professor at the Department of Electrical Engineering and Information Systems, University of Pannonia, and a research professor at the Process Control Research Group, Computer and Automation Research Institute, Hungarian Academy of Sciences. Professor Katalin Hangos, the head of the Intelligent Control Systems research laboratory, with her strong system- and control theoretical and computer science education, is one of the few female professors of the process control science. Her major field of interest is the dynamical modeling of process systems for control and diagnostic purposes. She is a coauthor of over 100 journal papers, about 200 conference publications and 3 books about different aspects of modeling and control of process systems including nonlinear, stochastic, Petri net-based, qualitative, and graph theoretical process models. She is the Hungarian representative of the IFAC Technical Committee on Chemical Process Control, and member of the IFAC Hungarian National Committee. She is the president of the Research Committee on Informatics of the Hungarian Academy of Sciences.
the project is supported
hungarys renewal
szechenyi plan
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