About department

Since 1981, Control Systems Research Laboratory conducted research on the development of the adaptive control systems theory for technical plants. Under the research supervision of Ye. Bodyanskiy, new principles of active-adaptive suboptimal control of stochastic dynamic plants using multi-step predictors in the circuit were developed. In this line of research, Ye. Bodyanskiy defended his doctoral dissertation in 1990.

In 1986–1990, CSRL was the head organization of 11 universities in Ukraine, Russia, Estonia, which were co-executors on the topic “Adaptive Control Systems”. Ye. Bodyanskiy was the deputy head of this topic and a member of the Inter-university Coordination Council of the USSR State Education Committee on “Integrated process control.”

In 1987 CSRL took part in creation of mathematical foundation for identification and control problems for the industrial plant PS-1 on the topic “Development of methods and tools for solving problems of identification and control of industrial processes on the basis of mathematical models.” (Participating countries: Bulgaria, Hungary, Mongolia, Poland, Romania, Czechoslovakia, USSR).

Under the Inter-university Program № 40 of Ministry of Education of Ukraine “Methods for the design and development of integrated computerized systems and technologies” for the state budget fundamental themes № 128 “Development of the theoretical foundation for control, monitoring and diagnostics systems in technical plants” (1991–1993, supervisor Ye. Bodyanskiy) and № 377 “Development of new principles of adaptive control of technical plants and processes under a priori uncertainty, taking into account different types of constraints and early fault diagnosis” (1994–1996, supervisor prof. Ye. Bodyanskiy) theoretical foundations of a new class of systems was created – self-diagnosing adaptive control systems designed for control and abnormal modes detection in real-time highly reliable systems, taking into account environmental constraints.

As a part of an integrated interfaculty state budget fundamental theme № 080 “Development of theoretical and mathematical foundations for adaptive neuro-and fuzzy- control systems subject to constraints on the basis of parametrically optimized controllers” (1997–2000, supervisor prof. Ye. Bodyanskiy), included in the Coordination plan № 9 of the Ministry of Education of Ukraine, fundamental research was carried out to develop effective methods for adaptive control of multi-dimensional stochastic dynamic plants under the constraints on state variables and errors, based on neuro-fuzzy technologies with advanced features.

As a part of an integrated interfaculty state budget fundamental theme № 132 “Development of theoretical and mathematical foundations of neuro-fuzzy systems for early diagnosis, prediction and simulation under a priori and current uncertainty” (2001–2003, supervisor Ye. Bodyanskiy) theoretical and mathematical foundations and methods were developed for neuro-fuzzy systems for early diagnosis, prediction, dynamic reconstruction, and modeling of time series of arbitrary nature (stochastic, deterministic, chaotic, quasiperiodic, and others) under a priori, current and parametric uncertainty. The design is based on the use of an ensemble of neural networks with different architectures (both universal and specialized) trained with different procedures and approaches that identify various hidden properties of the analyzed signals, thus providing an effective solution to the problem of prediction and early detection of the properties changes. The research provided fundamental results and contributed to the general theory of computational intelligence, in particular, the hybrid neuro-fuzzy systems. Scope: the automation of technological processes problem, mechatronics, biomedical, economic, financial and environmental series processing.

This research continued in an integrated state budget fundamental theme № 177 “Intelligent data mining and processing in real time based on computational intelligence tools” (2004–2006, supervisor Ye. Bodyanskiy) to develop new computational intelligence methods to solve a broad range of problems of real-time data analysis under the structural uncertainty. In particular, development of new neuro-, fuzzy-, neuro-fuzzy, neo-fuzzy, neuro-wavelet hybrid, adaptive systems for preprocessing, emulation, clustering, control, and compression of information given in an “object-property” tabular form, where the number of rows changes in time. The research results are intended for creation of competitive technologies of data mining and processing of biomedical, technological, economic information, in e-commerce, Web-mining, for creation of the corresponding software; students, postgraduates, and doctoral students training.

In 2008–2010, research continued in the framework of an integrated state budget fundamental theme № 214 “Synthesis of information processing methods under the uncertainty conditions based on self-learning and soft computing”, and since 2011 – an integrated state budget fundamental theme № 245 “Evolutionary hybrid computational intelligence systems with variable structure for data mining.”

Doctoral students, graduate students, and staff scientists take part in conducting the above research; 21 Ph.D. and 7 doctoral theses are defended in this scientific area.

Nine CSRL researchers are members of the IEEE Neural Network Society, Signal Processing Society, and Control Systems Society; one is a member of the European Neural Network Society.

The research results are published in a number of international and national academic titles (including “Radioelektronyka, informatyka, upravlinnya”, “Radioelektronyka i informatyka”, “ASU i pribory avtomatiki”, “Problemy bioniki”, “Elektronnoe modelirovanie”, “Dopovidi Natsionalnoi akademii nauk Ukrainy”, “Izvestiya vuzov. Priborostroenie”, “Problemy upravleniya i informatiki”, “Avtomatika i telemekhanika”, “Izvestiya RAN. Sistemy upravleniya”, “Visnyk KhGPU. Systemnyi analiz, upravlinnya i informatsiyni tekhnologii”, “Proceedings of ASI’98 “Life Cycle Approaches to Productions Systems”, Bremen, Germany”, “Proceedings Seventh Symp. on Artificial Intelligence and Neural Networks”, Ankara, Turkey, “Pattern Recognition and Image Analysis”, “J. of Computer and System Sci. International”, “Computational Intelligence and Applications”, Piraeus, Greece, “J. of Automation and Information Sci”, “Engineering Simulation”, “Computational Intelligence. Theory and Applications, Springer-Verlag, Berlin-Heidelberg, “Fluctuation and Noise Letters”, “Automation and Remote Control”, “Meme Media Laboratory, Hokkaido University, Sapporo”, “Proceedings of European Control Conference ECC’99”, Karlsruhe, Germany, “Proceedings of the 44-th, 45-th Internationales Wissenschaftliches Kolloquium, Vortragsreihen“, Ilmenau, Germany, “Proceedings of the First International Conference on Mechatronics and Robotics”, Saint-Petersburg, “Modeling and simulation of business systems”, Vilnius, Lithuania, “CIMCA Proceedings Intelligent Technologies. – Theory and Applications”, Amsterdam, Netherlands), are presented at conferences worldwide, including Ukraine, Russia, USA, Japan, England, Greece, Turkey, Finland, Slovakia, Germany, are presented at software exhibitions (there is a number of diplomas given to students and graduates), are used in a number of companies and organizations to solve real problems.

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