Head of the Research Laboratory
Katalin M. Hangos, DSc, Professor
The research laboratory carries out research in the interdisciplinary areas of systems and control theory, electrical engineering, energy systems and artificial intelligence. The research topics can be arranged along the following main directions.
1. Intelligent Diagnosis of Complex Systems
The diagnosis of complex large-scale industrial systems can only be carried out using heterogeneous information sources. In addition, the system to be diagnosed is characterized by its large scale and complexity, and the majority of the diagnostic information is heuristic, that results in the high computational complexity of the diagnosis problems. Therefore, model-based intelligent or discrete event system model (e.g. Petri net) based approaches are usually applied for the diagnosis of complex largescale industrial systems. The following specific research problems are investigated (see in details the research topic "Model Based Discrete Diagnosis"):
1.1. Fault detection and isolation using process mining approaches,
2.2. Risk assessment and analysis (FMEA es HAZOP) based diagnostic methods,
3.3. Diagnosis based on the reachability graph of Petri net system models.
2. Analysis, Identification and Control of Energy, Electrical and Quantum Systems
The state and parameter estimation of nonlinear stochastic systems has been an intensively studied research area nowadays, that presents nice theoretical challenges and has practical importance at the same time. Our research is directed towards the following lines:
2.1. Analysis and construction of complex electrical networks with renewable energy sources.
The aim of our research is to develop methods and procedures for optimally integrating renewable sources into an electrical network, and optimally operating generators and electrical accumulators using the concepts and tools of systems and control theory.
2.2. Nonlinear analysis and control of positive polynomial (reaction-kinetic and quasi-polynomial) systems.
Algebraic and graph-theoretical methods have been developed for structural stability analysis of positive polynomial systems, and static and dynamic polynomial stabilizing controllers and controller structures have been constructed based thereon. The results are applied for controller design of large-scale (bio)chemical reaction networks, as well as for energy and mechatronic systems.
2.3. State and parameter estimation of quantum systems.
The systems and control theoretical description of quantum systems presents serious challenges, because measurements applied for a quantum system acts on the system as a random disturbance making it a special stochastic system with output feedback. Convex optimization methods are applied for parameter estimation of quantum information processing channel, and for determining optimal measurement conditions for parameter estimation (i.e. for experiment design).
- Balló, G. & Hangos, K.M. (2012), "Convex Optimization-Based Parameter Estimation and Experiment Design for Pauli Channels", IEEE Transactions on Automatic Control. Vol. 57(8), pp. 2056-2061.
- Fodor, A., Magyar, A. & Hangos, K.M. (2012), "Control-oriented modeling of the energy-production of a synchronous generator in a nuclear power plant", Energy. Vol. 39, 135-145.
- Görbe, P., Magyar, A. & Hangos, K.M. (2012), "Reduction of power losses with smart grids fueled with renewable sources and applying EV batteries", Journal of Cleaner Production. Vol. 34, pp. 125-137.
- Hangos, K., Lakner, R. & Werner-Stark, A. (2012), "Modell alapú diagnosztika diszkrét módszerekkel Pannon Egyetem.
- Hannemann-Tamás, R., Gábor, A., Szederkényi, G. & Hangos, K.M. (2013), "Model complexity reduction of chemical reaction networks using mixed-integer quadratic programming", Computers & Mathematics with Applications, Vol. 65, pp. 1575-1595
Biography of the Head of the Laboratory
Katalin M. Hangos has an MSc in chemistry (ELTE TTK, 1976) and computer science (ELTE TTK, 1980). She has a DSc (1993), and habilitations (in chemical engineering in 1994, and in information technologies in 2000). She is now a full professor at the University of Pannonia, and a research professor at the Process Control Research Group of the Computer and Automation Research Institute of the Hungarian Academy of Sciences.