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Computerized control systems

1. General area

Computerized control systems.

2. The main research and development directions:

  • The study of methods for solving optimization control problems in systems with the linguistic and neural network models and stability problems under conditions of incomplete information about the controlled object;
  • Development of energy-efficient control systems for complex thermo technical objects with distributed parameters;
  • The development of neural network control systems for dynamic objects with a hardware-software implementation of the neural elements of the systems;
  • Development of methods and means of design and implementation of energy-efficient and optimal control in a multi-object distributed technical complexes;
  • Designing modern intelligent “smart house” type automation and scheduling systems;
  • Modeling, synthesis and practical implementation of integrated hardware and software solutions for building automation control systems for complex industrial facilities;
  • automation of engineering research in intelligent systems, data acquisition and process control;
  • algorithms and software design for control systems based on robotic hardware and software platforms;
  • Development and implementation of a new methodological support to the educational process on subject “Computerized control systems design.”


3. Main Results

  • The concept of solving optimization control problems with respect to of intellectual control systems in the form of structures, algorithms and synthesis of optimal systems stabilizing control methods for the conditions when the object is fully or partially unobserved, and data on the outputs of a complex controlled object are given as a linguistic (fuzzy) data;
  • The structure of intelligent control systems and algorithms for their operation based on a specialized programming environment that allows you to create on the basis of a priori information about the object and the conditions of its operation a direct and inverse linguistic model of a multidimensional controlled object are developed;
  • Methods and tools for neural network control systems synthesis based on hardware and hardware-software implementation of neural structures that are able to adjust in real time at the same pace as the controlled process that allows you to create adaptive control systems for complex dynamic objects based on the programmable logic. Software tools for modeling and configuration of neural network control systems elements as a whole are developed, that allows for quite easy synthesis, modeling, configuration and study of the neural network control systems and their networks on an engineering level; optimal structures of hardware-software implementation of neural network control systems elements and their functioning, learning procedures and adaptation algorithms developed and researched;
  • Software and hardware complex is created for the experimental study of the railway wagons wheel sets wearing off on the State Enterprise “State Research Center of Railway Transport of Ukraine” (Kyiv);
  • Designed and implemented an automated control system of technological systems for growing artificial diamonds at the Institute for Superhard Materials of NaSU (Kyiv);
  • Created methodological support for laboratory and practical work in teaching 2 subjects: “Computerized control systems design “and” artificial intelligence technologies in control”.


Scientific publications in the direction of “Computerized Control Systems”