In the first year of study, student chooses three courses from the first year of their chosen domain (Control systems).
In the second year, student chooses three courses from the group of all elective courses at second year of doctoral academic studies, regardless of the elective domain the course belongs to.
1. YEAR
Elective Block (3 out of 7)
Code: 3DЕU1I01
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:System definition, examples, history, importance and classification of control systems. The basic principles of control. Mathematical description of dynamical systems. A uniform approach to system analysis. Basic system performances. Technical requirements specification and principles of control system design. Performance evaluation. Some engineering problems. MATLAB implementations.
Code: 3DEU1I02
Number of classes per week:
- Lectures: 3
- Exercises:0
ECTS: 10
Course outline:Plants classification. Identification algorithms and their convergence. Active identification. Gradient methods of identification. Single and multidimensional regression models. Nonlinear regression method. Iterative identification methods. Passive identification. Experiment planning. Forming of optimal identification algorithms. Theoretical background for Legendre, Laguerre, Chebyshev orthogonal polynomials. Design of almost and quasi orthogonal polynomials and their application in identification real dynamical systems. Application of orthogonal functions and filters in identification systems. Methods for assessing the quality of identification.
Specification for the book of courses
Code: 3DЕU1I03
Number of classes per week:
- Lectures: 3
- вежбе: 0
- други облици наставе: 0
ЕСПБ: 10
Градиво:Model uncertainties of linear dynamical systems and their representation in time and frequency domain. H2 and H∞ spaces and norms. Specifications of performances and limitations. Control plant model reduction. Model uncertainties and robustness. Robust stability and performance analysis. Linear fractional transformations. Structured singular value. Controller parameterization. Algebraic Riccati equation. H2 и H∞ control. Controller order reduction. H∞ loop-shaping.
Code: 3DEU1I04
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:Problems of managing complex technological processes. Centralized management. Distributed management. Hierarchical management. Chosing real-time PCs. Input output devices. Real-time system software support. Merging computers with technological processes. Application of microcomputers in the design and implementation of control systems. Application of PLC and SCADA system in process management. Application of computers in the process industry, in the management of dislocated objects and in the management of utility systems.
Specification for the book of courses
Code: 3DЕU1I05
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:Problems of managing complex technological processes. Centralized management. Distributed management. Hierarchical management. Chosing real-time PCs. Input output devices. Real-time system software support. Merging computers with technological processes. Application of microcomputers in the design and implementation of control systems. Application of PLC and SCADA system in process management. Application of computers in the process industry, in the management of dislocated objects and in the management of utility systems.
Code: 3DEU1I06
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:Intelligent systems for classification and database optimization. Types of neural network learning. Recommender systems. Large Scale Machine Learning. Hybrid Intelligent Systems. ANFIS.
Code: 3DEU1I07
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:Introduction: Mechatronic systems and review of linear systems. Minimal realizations of linear systems and Kalman decomposition. Function of matrices and phase portraits of linear systems. Phase portraits of nonlinear systems. Bifurcation theory. Lyapunov stability. Lie brackets and feedback linearization. Sliding mode control. Disturbance rejection. Systems with multiple inputs and multiple outputs. The principle of optimality. Linear Quadratic Regulation and Tracking. Introduction to digital control and z-domain. Digital control system design.
Obligatory
Code: 3DNIR1
Number of classes per week:
- Study and research work: 11
ECTS: 30
Course outline:Specification for the book of courses
3. YEAR
Obligatory
Code: 3DNIR2
Number of classes per week:
- Study and research work: 11
ECTS: 30
Course outline:Specification for the book of courses
Code: 3DZR
Number of classes per week:
- Lectures: 0
- Exercises: 0
ECTS: 30
2. YEAR
Elective Block (3 out of 82)
Courses from the chosen domain (Control systems)
Code: 3DEU3I01
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:Modern theory of digital control systems. Sampling in digital signal processing and digital control theory. Uniform approach to the analysis and synthesis of digital control systems. Some elements of analysis and synthesis of nonlinear digital control systems.
Code: 3DEU3I02
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:Calculus of variations. Maximum principle. Normal and singular problem of optimal control. Structure and design of optimal controllers. Selected topics in dynamical systems optimization. Dynamic programming. Hamilton-Jacobi-Bellman differential equation. Optimal solution as a function of the state vector. Singular control in some linear systems with quadratic cost function. Optimal control in digital systems.
Specification for the book of courses
Code: 3DEU3I03
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:The concept of variable structure systems and sliding mode. Continuous- and discrete-time sliding modes. Quasi sliding modes. Characteristics of systems with sliding mode control. Invariance conditions. Problems of mathematical description of sliding mode. Filippov's method. Equivalent control method. Stability of the systems with the sliding mode control. Systems with scalar and vector control. Methods for realization of sliding mode control in multivariable systems. Chattering reduction. Problems of realization of systems with sliding mode control. Sliding mode control in systems with finite zeros. Realization of sliding mode control based only on measuring of plant inputs and outputs. Examples of practical implementation of sliding mode control.
Specification for the book of courses
Code: 3DЕU3I04
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:Configuration of distributed control systems. Communication networks. Control algorithms in distributed control systems. Economic justification of distributed management. Evaluation of distributed computer control systems. Microcomputer control networks. Trends in distributed computer management.
Specification for the book of courses
Code: 3DEU3I05
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:Robust model predictive control. Types of uncertainty. Feedback versus open-loop control. Nominal robustness. Robust MPC design of nonlinear systems. State estimation. Moving horizon estimation (MHE). Extended Kalman filtering. Particle filtering. Combined MHE/particle filtering. Output MPC. Linear constrained systems. Offset-free MPC. Nonlinear constrained systems. Distributed MPC (DMPC). Introduction and consideration of the existing results. Unconstrained two-player game. Constrained two-player game. Constrained M-player game. Nonlinear DMPC. Explicit control laws for constrained linear systems.
Specification for the book of courses
Code: 3DEU3I06
Number of classes per week:
- Lectures: 3
- Exercises: 0
ECTS: 10
Course outline:
Parameter estimation in real time. On-line parameter estimation: gradient methods and least squares methods in continuous and discrete time. Parameter estimation with projection. Extremum seeking methods. Self-tuning regulators. Direct and indirect adaptive control: pole placement control (PPC), adaptive pole placement control (APPC), model reference control (MRC), model reference adaptive control (MRAC), adaptive backstepping with tuning functions. Machine learning methods: neuroadaptive control and reinforcement learning control. Practical aspects and implementation of adaptive control systems and introduction to computational learning theory.Specification for the book of courses
Groups of courses from all other domains
- Electrical Machines and Transformes - Selected Chapters
- Electrical Machines and Power Converters for Renewable Energy Sources
- Digital Control of Electrical Drives and Power Converters
- Computation of Lightning Overvoltages
- Power Cable Engineering
- Power Quality in Distribution Networks
- Active Distribution Networks and Microgrids
- Digital Processing of Audio Signal
- Digital Circuits and Systems Design
- Embedded Systems Design
- System-on-Chip Design
- DSP Architectures and Algorithms
- Electronic Circuits Testing
- Reconfigurable Systems Synthesis of Filters
- RF Systems Architectures
- Computer Vision
- Ultrasonic Technique
- Measurement and Acquisition Systems
- Industrial Measurement and Information Systems
- Measurement and Information Technologies
- Medical and Bioelectronic Measurement Technique
- Power Devices and Circuits
- Microsensors
- Reliability of Electronic Devices and Microsystems
- Prognosis of the Material Properties
- Advanced Electronic Ceramic Materials
- Software Engineering in Microelectronics
- Solar Systems, Technologies and Devices
- Technology, Design and Characterization of Microsystems
- Reliability Modeling of MOS Devices
- Influence of Radiation on Microelectronic Devices
- Mathematical Methods of Optimization
- Analysis of Numerical Algorithms
- Spectral graph theory
- Highly Efficient Iterative Methods
- Simulation of Industrial Systems
- Mathematical Models in Industry
- Mathematical Foundations of Statistical Learning and Applications
- Devices of Vacuum and Gas Electronics
- Medical Physics
- Semiconductor Devices and Technologies
- Sensors and Actuators
- Technological Processes in Gasses and Vacuum
- Design and Analysis of Parallel Algorithms
- Advanced Topics in Fault Tolerant System Design
- Bioinformatics
- Medical Informatics
- Applications of Spectral Techniques for Digital Devices Design
- Advanced Topics in Mobile and Ubiquitous Computing
- Advanced Topics in Computer Graphics
- Advanced Topic in Intelligent Systems
- Advanced Topics in Specialized Information Systems
- Mathematical Fundament of the Game Theory
- Advanced Topics in E-Learning Technologies
- Web Mining and Information Retrieval
- Audio Communications
- Antennas and Propagation
- Applications of Neural Networks in Telecommunications
- Satellite Communication Systems
- RF and Microwave Amplifiers
- Electromagnetic Compatibility and Signal Integrity
- Detection of Signals in Noise
- Communication Algorithms and Applications
- 5G and 6G Mobile Communications
- Information Theory and Source Coding
- Statistical Signal Processing
- Digital Communications Over Fading Channel
- Coherent Optical Telecommunication Systems
- Theory and Applications of Software Radio
- Advanced Modeling Techniques for RF Applications
- Free-space Optical Telecommunications
- Advanced Signal and Data Processing
- Methods for Steady-state Electromagnetic Fields Calculation
- Inverse problems in Electromagnetics
- Bounday Element Method in Electromagnetics
Obligatory
Code: 3DNIR2
Number of classes per week:
- Study and research work: 11
ECTS: 30
Course outline:Specification for the book of courses
Doctor of Science in electrical engineering and computing