Code PSL126B
Course unit Applied problems and methods of optimization of complex electromechanical systems
Nomber of credits ECTS 5.0
Language of education Ukrainian
Learning outcomes of course unit

The aim of the discipline is to provide master’s and postgraduate students with both theoretical and practical knowledge related to current issues in the synthesis of optimal automatic control systems, taking into account the specific properties of controlled objects. In particular, modern switched‑reluctance motors and permanent‑magnet brushless motors, systems with distributed parameters, or cascaded connections of subsystems require enhanced mathematical descriptions to ensure optimal technical and energy performance in dynamic and quasi‑static modes. Such improvements are achieved through the use of fractional‑order differential equations. Accordingly, controllers for these objects are designed as fractional‑integral or fractional‑differential regulators. The application of such regulators significantly expands the possibilities for optimizing the operation of electric drives and automatic control systems as a whole, but also requires solving specific problems of fractional integral computation and controller programming. The practical component of the course provides students with experience in configuring single‑chip and industrial controllers for the control of such systems. A substantial portion of the teaching material is based on the department’s own scientific achievements in this research area.

Types of educational work Lectures. Practical classes. Laboratory work. Independent work.
Type of final control
Content of course unit

Theoretical foundations of fractional calculus.

Synthesis of fractional‑integral and fractional‑differential regulators.

Methods for solving fractional‑order differential equations.

Modeling of closed‑loop control systems for brushless DC motors and series‑excited motors.

Principles of programming controllers for the implementation of fractional‑integral and fractional‑differential regulators.

Equipment (if applicable)    РС, Matlab, Neural network toolbox MATLAB Online https://matlab.mathworks.com SCADA Citect Vijeo v.7.40

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