Automation
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DepartmentFaculty of Electronics
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Program code6211EX048
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Field of studyEngineering
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QualificationMaster of Engineering Sciences
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Duration2
About
AUTOMATION
| Degree | Master of Engineering Sciences |
| Length | 2 years (4 semesters) |
| Study language | Lithuanian |
| Start | 1st of September |
| Entry Qualification | To this programme applicants are accepted from the fields of: Electronics Engineering, Power Engineering, Electrical Engineering, Information Systems, Software Engineering, Informatics Engineering, Mechanical Engineering, Production and Manufacturing Engineering, Transport engineering, Physics. |
Digital automation technologies accompany modern human beings at every turn they take – from the simplest household appliances to automated manufacturing complexes.
All successfully applied solutions not only facilitate or free one from physical labor altogether, but also create opportunities to develop new quality products, save time, energy and raw materials, at the same time making the process itself flexible and secure.
The aim of the Master's study program in Automation is to provide the latest knowledge in electrical engineering and related fields of study, develop the ability to seek new knowledge while conducting research, develop automatic and mechatronic systems and update professional competence.
Students in this Master's program will have the opportunity to choose one of the two specializations – Automation Systems or Automation of Mechatronic Systems.
Students opting for the specialization in Automation systems will acquire the competencies in designing, operating, and improving modern continuous and discrete automation control systems. Such systems are based on the latest control technologies using neural networks and fuzzy logic.
Automation systems not only make our daily work more convenient, but also facilitate performance of various production processes, enhancing their safety, accuracy and efficiency.
With the technological advancement, modern control systems engineering has become one of the fastest growing areas. Without automation control, it would be impossible to communicate via satellites or space launch of a spacecraft.
Today, automation control systems can be found in all industries, from automated assembly lines to robotics or nanotechnology.
Students specializing in Automation of Mechatronic Systems will gain skills and understanding in the following areas of expertise: design, operational maintenance and further development of a variety of modern mechatronic systems controlled by programmable logic controllers and embedded computers.
Specialists in this field are responsible for the installations and equipment in all phases of their life cycle – from design, installation, operational maintenance, further development to recycling.
Typical examples of mechatronic systems range from the simplest 3D printers to industrial robots and autonomous vehicles.
What competencies will I acquire?
The Master's Degree Program in Automation is designed to gain the following skills:
- to carry out specialized research activities;
- to interpret data, select and apply mathematical methods, software and hardware aimed at solving and analyzing engineering problems;
- to design, maintain and operate as well as further develop modern continuous-time and discrete-time automatic control systems;
- to design, maintain and operate as well as improve various modern mechatronic systems controlled by programmable logic controllers and embedded computers.
What are my possible career pathways?
- Working and managing divisions in companies specializing in design, modernization or operation of automated equipment, automation and mechatronic systems.
- Working in transport, energy, construction, communications companies.
- Pursuing doctoral studies in the chosen field of technology.
Study subjects
1 Semester
obligatory
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ELEIM17151 9 credits
Electronic Power Converters
Module aim
Deepen knowledge in power electronics, acquire abilities to evaluate results of calculations and experimental investigations and interpret this information for solving given tasks, to use mathematical methods, software and technical equipment for modelling, design, diagnostics and obtained result processing, to function individually and in the team, responsively, thoroughly and ability communicate with colleagues and specialists of adjacent areas.
Module description
Devices, structure and elements of modern power electronics. Control and applications of electronic power converters. Power electronics of renewable energy resources. Mathematical models of electronic power converters.
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ELKRM17107 6 credits
Computers and Their Systems in Automation
Module aim
Provide graduate students theoretical knowledge and practical skills necessary to design and implement computer-aided control and SCADA systems, as well as to absorb their associated design methods, software principles.
Module description
Computers and their Systems in the Electrical Engineering Knowledge on: classification of computer, architecture and the main computer unit (CPU, bus, memory subsystem, disk storage subsystem) functioning principles, OSI model, computer network topologies and protocols, industrial computer networks, popular automation interfaces , Supervisory Control And Data Acquisition systems (SCADA systems) design principles and software, distributed control (DCS) and emergency shutdown (ESD) systems and the principles of hardware and software features
Students must complete no less than 80% of the scheduled laboratory works -
ELKRM17103 6 credits
Mathematical Modelling Technologies
Module aim
To learn design and develop mathematical models of electronic circuits and systems using modern modeling technologies, critically analyze modeling results and draw conclusions.
Module description
Mathematical modelling technologies subject delivers knowledge about mathematical modelling, numerical methods, application of linear and nonlinear equations, matrices and differential equations for description and numerical modelling of electronic circuits and systems, numerical integration and differentiation, data processing, analysis and visualization.
Students must complete no less than 80% of the scheduled laboratory works -
ELESM17103 6 credits
Fundamentals of Research and Innovations
Module aim
To deliver knowledge about research, development and innovation systems, to develop scientific work planning, performing and organizing skills and scientific results public presentation abilities.
Module description
Fundamentals of Research and Innovations subject delivers knowledge about research, development and innovation systems, inventions and patents, engineering ethics and decision making in engineering, scientific document preparation and presentation. Recognition and analysis of the new and significant in electronics and informatics engineering field research and development problems are taught. Skills to plan, perform and organize scientific work are exercised. Abilities to prepare and present public presentations and posters, work in a team, communicate with colleagues and be in charge of others work are developed. Students must attend at least 80% of the course laboratory and at least half of the lectures according to the semester schedule.
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ELEIM17152 3 credits
Master's Research Work 1
Module aim
Perform research in the application field of automatic systems, summarize research results and prepare technical report of Graduation Work demonstrating abilities to integrate knowledge acquired during studies, and work individually or in team, and by successful defence of Master’s Graduation Work proof achievement of goals of study program.
Module description
Set up together with supervisor of topic of Master’s Graduation Thesis. Gather initial data on Graduation Thesis topic. Compose and set up of task of Graduation Thesis. Analysis of literature and Graduation Thesis task. Set up of timetable of preparation of Graduation Thesis. Acquiring knowledge about design and programming of automatic systems, scientific investigation and experimentation. Elevate ability to combine theoretical and practical elements, to apply information technologies, to assess and analyze literature and data. Preparation of technical report.
obligatory
-
ELEIM17151 9 credits
Electronic Power Converters
Module aim
Deepen knowledge in power electronics, acquire abilities to evaluate results of calculations and experimental investigations and interpret this information for solving given tasks, to use mathematical methods, software and technical equipment for modelling, design, diagnostics and obtained result processing, to function individually and in the team, responsively, thoroughly and ability communicate with colleagues and specialists of adjacent areas.
Module description
Devices, structure and elements of modern power electronics. Control and applications of electronic power converters. Power electronics of renewable energy resources. Mathematical models of electronic power converters.
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ELKRM17107 6 credits
Computers and Their Systems in Automation
Module aim
Provide graduate students theoretical knowledge and practical skills necessary to design and implement computer-aided control and SCADA systems, as well as to absorb their associated design methods, software principles.
Module description
Computers and their Systems in the Electrical Engineering Knowledge on: classification of computer, architecture and the main computer unit (CPU, bus, memory subsystem, disk storage subsystem) functioning principles, OSI model, computer network topologies and protocols, industrial computer networks, popular automation interfaces , Supervisory Control And Data Acquisition systems (SCADA systems) design principles and software, distributed control (DCS) and emergency shutdown (ESD) systems and the principles of hardware and software features
Students must complete no less than 80% of the scheduled laboratory works -
ELKRM17103 6 credits
Mathematical Modelling Technologies
Module aim
To learn design and develop mathematical models of electronic circuits and systems using modern modeling technologies, critically analyze modeling results and draw conclusions.
Module description
Mathematical modelling technologies subject delivers knowledge about mathematical modelling, numerical methods, application of linear and nonlinear equations, matrices and differential equations for description and numerical modelling of electronic circuits and systems, numerical integration and differentiation, data processing, analysis and visualization.
Students must complete no less than 80% of the scheduled laboratory works -
ELESM17103 6 credits
Fundamentals of Research and Innovations
Module aim
To deliver knowledge about research, development and innovation systems, to develop scientific work planning, performing and organizing skills and scientific results public presentation abilities.
Module description
Fundamentals of Research and Innovations subject delivers knowledge about research, development and innovation systems, inventions and patents, engineering ethics and decision making in engineering, scientific document preparation and presentation. Recognition and analysis of the new and significant in electronics and informatics engineering field research and development problems are taught. Skills to plan, perform and organize scientific work are exercised. Abilities to prepare and present public presentations and posters, work in a team, communicate with colleagues and be in charge of others work are developed. Students must attend at least 80% of the course laboratory and at least half of the lectures according to the semester schedule.
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ELEIM17152 3 credits
Master's Research Work 1
Module aim
Perform research in the application field of automatic systems, summarize research results and prepare technical report of Graduation Work demonstrating abilities to integrate knowledge acquired during studies, and work individually or in team, and by successful defence of Master’s Graduation Work proof achievement of goals of study program.
Module description
Set up together with supervisor of topic of Master’s Graduation Thesis. Gather initial data on Graduation Thesis topic. Compose and set up of task of Graduation Thesis. Analysis of literature and Graduation Thesis task. Set up of timetable of preparation of Graduation Thesis. Acquiring knowledge about design and programming of automatic systems, scientific investigation and experimentation. Elevate ability to combine theoretical and practical elements, to apply information technologies, to assess and analyze literature and data. Preparation of technical report.
2 Semester
obligatory
-
ELEIM17253 9 credits
Advanced Automatic Control Systems (with Course Project)
Module aim
Learn to design and analyze advanced automatic control systems, design controllers, based on fuzzy logic and neural networks matching specifications of control system, apply those for control of various dynamic systems and get ability to use advanced informational technologies, design systems with incompletely defined information.
Module description
The deep knowledge about mathematical modeling of advanced automatic control systems is provided: description of systems by differential equations, transfer functions and state space variables; analysis of the system and design of controllers by root locus method, design of controllers by state variables method; design of controllers based on fuzzy logic and neural networks.
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ELEIM17252 6 credits
Micromachines for Automation
Module aim
Acquire knowledge about micromotors of automatic and electromechanical converters of mechatronic systems, their types, construction, control modes, acquire ability to understand theoretically the newest technologies of electrical engineering.
Module description
Knowledge are provided about modern micromotors of automatic, about their posibilities and application areas. Consideration the design and operating principles of the direct and alternating current micromotors ang presents the main expressions and characteristics. The main terms in Lithuanian, English and German are presented and their definitions are discussed.
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ELEIM17251 6 credits
Neural Networks and Fuzzy Logic in Automation
Module aim
To provide the student with knowledge about neuron, its mathematical model, neural networks and fuzzy logic. To teach students to model the neural network with computers and solve tasks of systems identification. To provide the students the knowledge about fuzzy sets, actions with them and their application for controllers design.
Module description
Neuron, its structure and mathematical model; neural networks and its topologies; multilayer perceptron; learning of neural network; neural networks for systems identification; neural control; fuzzy sets theory; fuzzy logic for control; fuzzy control.
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ELEIM17257 3 credits
Master's Research Work 2
Module aim
Perform research in the application field of automatic engineering, summarize research results and prepare technical report of Graduation Work demonstrating abilities to integrate knowledge acquired during studies, and work individually or in team, and by successful defence of Master’s Graduation Work proof achievement of goals of study program.
Module description
Acquiring new knowledge about design and programming of automatic systems, scientific investigation and experimentation. Elevate ability to combine theoretical and practical elements, to apply information technologies, to assess and analyze literature and data. Preparation of second technical report.
obligatory
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ELEIM17255 9 credits
Modelling of Mechatronic Systems (with Course Project)
Module aim
Acquire knowledge about modeling methods of mechatronic system elements and overall system; learn to develop models of dynamic systems describing them by transfer functions or state space variables. Acquire ability fulfill system analysis and design, based on modeling; develop new models and apply them for systems control.
Module description
Role of the models in development of mechatronic systems. Elaborating of mathematical models of mechatronic systems. Description of systems by differential equations, transfer functions, state space variables. MIMO and SISO systems. Getting of transfer function and characteristic polynomial from system state space model. Control with state space feedback, Akkerman’s formula. Full order and reduced order observers. Models of linear mechatronic systems.
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ELEIM17254 6 credits
Electromechanical Elements of Mechatronics
Module aim
Acquire knowledge about electromechanical converters of mechatronic elements, their types, construction, control modes, acquire ability to understand theoretically the newest technologies of electrical engineering, ability to communicate, present work results to for specialists of neighboring areas, provide consultations in the area of activity in development of mechatronic systems.
Module description
Theoretical knowledge is provided about power equipment and devices of mechatronic systems :direct current motors, alternating current motors, special motors, direct or alternating current actuators, piezomotors and piezoactuators, their control, their electromechanical properties and devices providing feedback in mechatronic systems: converters of rotational speed and position: tachogenerators, encoders, synchros and resolvers, principle of their operation and application areas. The main terms in Lithuanian, English and German are presented and their definitions are discussed.
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MERSM17167 6 credits
Mechanics of Mechatronical Systems
Module aim
To get acquainted with the structure of mechatronical systems, their constituent parts, methods of estimation of the mechanical part of mechatronical system during the analysis of mechatronical system operation. To get acquainted with simulation of mechatronic systems.To get acquainted with the robot structure, principles of their creation, calculations, which are peformed during the robot designing, sensors used in robotic systems, actuators, control systems used for robots. To present informa
Module description
Mechanical elements, structure, principles of design, components of mechatronic systems. Constituent parts of robots, their structure and composition principles. Determination of robot positioning accuracy. Direct and inverse kinematic problems of manipulators, the velocity problem, problems of static forces, dynamic problems. The mechanical system of robots, their execution system and their strength calculations. Grippers of robots and principles of their calculations. Sensors. The robot control system.
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ELEIM17257 3 credits
Master's Research Work 2
Module aim
Perform research in the application field of automatic engineering, summarize research results and prepare technical report of Graduation Work demonstrating abilities to integrate knowledge acquired during studies, and work individually or in team, and by successful defence of Master’s Graduation Work proof achievement of goals of study program.
Module description
Acquiring new knowledge about design and programming of automatic systems, scientific investigation and experimentation. Elevate ability to combine theoretical and practical elements, to apply information technologies, to assess and analyze literature and data. Preparation of second technical report.
one of the following
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ELESM17215 6 credits
Algorithms and Data Structures
Module aim
To grasp fundamentals of one-dimensional and multidimensional data structures, to develop algorithms based on these data structures, and to apply these algorithms in structured and semistructured information search, data base indexing, digital image processing, computer graphics and vision, while being able to reason the chosen technical solutions.
Module description
In this course are presented logical and hierarchical data structures, sorting and search techniques and algorithms for sequence processing and compression. Reviewed applicability analysis of these basic algorithms for the construction of the more sophisticated application-oriented algorithms (structured and semistructured information search, data base indexing, digital image processing, computer graphics and vision).Effect of the nature of applications on algorithm formalization and their sophistication analysis is also presented. Students must complete all scheduled laboratory work. Students must attend at least 80% of the course laboratory and at least half of the lectures according to the semester schedule.
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ELEIM17200 6 credits
Systemotechnique and Sensors
Module aim
To analyze principles of work of gauges and converters, to be able to project circuits of the automated measurement and control.
Module description
Resistive, inductive, capacitor, photoelectric gauges used in power electronics. DAC and ADC. Microprocessors and use of him for processing the information and control.
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ELEIM17256 6 credits
Modern Electric Drives
Module aim
Acquire knowledge about performance and control methods of modern electric drives; learn to use them in practice. Learn to choose drive and its elements according to specification of technological process. Acquire knowledge about vector and direct torque and flux control, sensor-less control, Fuzzy control and principles of development of Fuzzy controllers, learn to develop computer models of electric drives, and ability to work individually and in a team.
Module description
Fundamental Knowledge of Modern Electric Drives, Their Structure and Characteristics, and Drive Control Methods: Vector Control of Induction Drives, Direct Torque and Flux Control. Application of Fuzzy Logic in Electric Drive Control, Principles of Fuzzy Controller Design, Control of DC and Induction Drives Using Fuzzy Controllers. Sensorless Drives. Drives for Modern Tracking and Positioning Systems, as well as Mathematical and Simulation Models of Electric Drives.
one of the following
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ELESM17215 6 credits
Algorithms and Data Structures
Module aim
To grasp fundamentals of one-dimensional and multidimensional data structures, to develop algorithms based on these data structures, and to apply these algorithms in structured and semistructured information search, data base indexing, digital image processing, computer graphics and vision, while being able to reason the chosen technical solutions.
Module description
In this course are presented logical and hierarchical data structures, sorting and search techniques and algorithms for sequence processing and compression. Reviewed applicability analysis of these basic algorithms for the construction of the more sophisticated application-oriented algorithms (structured and semistructured information search, data base indexing, digital image processing, computer graphics and vision).Effect of the nature of applications on algorithm formalization and their sophistication analysis is also presented. Students must complete all scheduled laboratory work. Students must attend at least 80% of the course laboratory and at least half of the lectures according to the semester schedule.
-
ELEIM17200 6 credits
Systemotechnique and Sensors
Module aim
To analyze principles of work of gauges and converters, to be able to project circuits of the automated measurement and control.
Module description
Resistive, inductive, capacitor, photoelectric gauges used in power electronics. DAC and ADC. Microprocessors and use of him for processing the information and control.
-
ELEIM17256 6 credits
Modern Electric Drives
Module aim
Acquire knowledge about performance and control methods of modern electric drives; learn to use them in practice. Learn to choose drive and its elements according to specification of technological process. Acquire knowledge about vector and direct torque and flux control, sensor-less control, Fuzzy control and principles of development of Fuzzy controllers, learn to develop computer models of electric drives, and ability to work individually and in a team.
Module description
Fundamental Knowledge of Modern Electric Drives, Their Structure and Characteristics, and Drive Control Methods: Vector Control of Induction Drives, Direct Torque and Flux Control. Application of Fuzzy Logic in Electric Drive Control, Principles of Fuzzy Controller Design, Control of DC and Induction Drives Using Fuzzy Controllers. Sensorless Drives. Drives for Modern Tracking and Positioning Systems, as well as Mathematical and Simulation Models of Electric Drives.
3 Semester
obligatory
-
ELEIM17351 9 credits
Discrete Control Systems
Module aim
Learn to design and analyze discrete control systems, design controllers matching specifications of discrete control system, apply those for control of various dynamic systems and get ability to use advanced informational technologies, design systems with incompletely defined information.
Module description
Subject “Discrete control systems” provides knowledge about design strategies of discrete control systems, block diagrams, the basis of mathematical models of systems: differential equations of discrete systems, discrete Laplace transform, transfer functions and stability analysis in frequency domain (Mikhailov, Nyquist methods) and Bode diagrams; and knowledge, required for system synthesis: principles of designing of proportional, integral, integral proportional and proportional integral derivative controllers and compensating elements; knowledge about modeling of transient processes using MATLAB software.
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ELEIM17352 9 credits
Engineering Systems of Industrial Automation (with Course Project)
Module aim
Engineering system of industrial automation structures diagrams. Engineering system of industrial automation modeling, task determination criterion and methods. Controllers of engineering system of industrial automation, tools for programming and adjustment: requirement and selection methodic. Optimization of control system. Automation of engineering system of industrial automation by applying non-traditional actuators.
Module description
Engineering system of industrial automation structures diagrams. Engineering system of industrial automation modeling, task determination criterion and methods. Controllers of engineering system of industrial automation, tools for programming and adjustment: requirement and selection methodic. Optimization of control system. Automation of engineering system of industrial automation by applying non-traditional actuators.
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ELEIM17357 3 credits
Master's Research Work 3
Module aim
Perform research in the application field of automatic engineering, summarize research results and prepare technical report of Graduation Work demonstrating abilities to integrate knowledge acquired during studies, and work individually or in team, and by successful defence of Master’s Graduation Work proof achievement of goals of study program.
Module description
Acquiring new knowledge about design and programming of automatic systems, scientific investigation and experimentation. Elevate ability to combine theoretical and practical elements, to apply information technologies, to assess and analyse literature and data. Preparation of second technical report.
obligatory
-
ELEIM17351 9 credits
Discrete Control Systems
Module aim
Learn to design and analyze discrete control systems, design controllers matching specifications of discrete control system, apply those for control of various dynamic systems and get ability to use advanced informational technologies, design systems with incompletely defined information.
Module description
Subject “Discrete control systems” provides knowledge about design strategies of discrete control systems, block diagrams, the basis of mathematical models of systems: differential equations of discrete systems, discrete Laplace transform, transfer functions and stability analysis in frequency domain (Mikhailov, Nyquist methods) and Bode diagrams; and knowledge, required for system synthesis: principles of designing of proportional, integral, integral proportional and proportional integral derivative controllers and compensating elements; knowledge about modeling of transient processes using MATLAB software.
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ELEIM17353 9 credits
Control of Mechatronic Systems (with Course Project)
Module aim
Learn to design and analyze advanced mechatronic systems described by different modes: transfer functions, state-space variables, design controllers, matching specifications of control system based on root locus method, apply those and observers for control of various mechatronic systems and get ability to use advanced informational technologies, design systems with incompletely defined information.
Module description
The deep knowledge about mathematical modeling of mechatronic systems elements and mechatronic automatic control systems is provided: description of systems by differential equations, transfer functions and state space variables; analysis of the system and design of controllers by root locus method, design control systems with observers by state variables method, design of feedback.
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ELEIM17357 3 credits
Master's Research Work 3
Module aim
Perform research in the application field of automatic engineering, summarize research results and prepare technical report of Graduation Work demonstrating abilities to integrate knowledge acquired during studies, and work individually or in team, and by successful defence of Master’s Graduation Work proof achievement of goals of study program.
Module description
Acquiring new knowledge about design and programming of automatic systems, scientific investigation and experimentation. Elevate ability to combine theoretical and practical elements, to apply information technologies, to assess and analyse literature and data. Preparation of second technical report.
one of the following
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ELEIM17302 6 credits
Electromagnetic Pulse Power Technologies
Module aim
To get to know high-power devices, areas of their application, to learn to estimate limiting parameters of devices.
Module description
Introduction to electrical breakdown in gases, liquids and solid state materials, optically and electrically induced phase transitions in semiconductors, in superconductors, shock waves action on electrical conductivity of semiconductors, dielectrics, ferroelectrics and ferromagnetics and application of these effects for magnetic flux compression. High power electric and magnetic field values measurements and pulse-power electronics devices.
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ELESM19308 6 credits
Evolutionary Computation and Agent Systems
Module aim
To learn define, project, create, improve and apply various evolutionary computation algorithms and agent systems, know how to explain proposed solutions, analyze examples, while working in a group or individually.
Module description
Evolutionary computation and agent systems module develops knowledge of genetic algorithms, evolutionary strategies, genetic programing, agents, multi-agent systems and other metaheuristics algorithm based system elements and working principles. In the study course, skills for analyzing specific examples, defining and understanding advantages and disadvantages of evolutionary algorithms are developed. Additionally, skills to practically apply evolutionary computation and agent systems using MATLAB software is improved, along with skills to practically solve tasks which require artificial intelligence. Students must complete all scheduled laboratory work. Students must attend at least 80% of the laboratory and at least half of the lectures according to the semester schedule.
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ELKRM17308 6 credits
Data Mining Techniques
Module aim
To provide knowledge about data mining methods used to reveal objectively existing patterns into various nature datasets, to develop the ability to select and apply the suitable data mining method for particular task.
Module description
Module content is focused on modern data mining techniques and their application to find previously unknown and potentially useful information analysing big data sets. Module content includes: data preprocessing and exploratory data analysis, classification methods (nearest neighbour’s method, naive Bayes classifier and decision trees), regression analysis, data clustering and evaluation of model performance.
Students must participate in no less than 80% of the scheduled practical works
one of the following
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ELEIM17302 6 credits
Electromagnetic Pulse Power Technologies
Module aim
To get to know high-power devices, areas of their application, to learn to estimate limiting parameters of devices.
Module description
Introduction to electrical breakdown in gases, liquids and solid state materials, optically and electrically induced phase transitions in semiconductors, in superconductors, shock waves action on electrical conductivity of semiconductors, dielectrics, ferroelectrics and ferromagnetics and application of these effects for magnetic flux compression. High power electric and magnetic field values measurements and pulse-power electronics devices.
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ELESM19308 6 credits
Evolutionary Computation and Agent Systems
Module aim
To learn define, project, create, improve and apply various evolutionary computation algorithms and agent systems, know how to explain proposed solutions, analyze examples, while working in a group or individually.
Module description
Evolutionary computation and agent systems module develops knowledge of genetic algorithms, evolutionary strategies, genetic programing, agents, multi-agent systems and other metaheuristics algorithm based system elements and working principles. In the study course, skills for analyzing specific examples, defining and understanding advantages and disadvantages of evolutionary algorithms are developed. Additionally, skills to practically apply evolutionary computation and agent systems using MATLAB software is improved, along with skills to practically solve tasks which require artificial intelligence. Students must complete all scheduled laboratory work. Students must attend at least 80% of the laboratory and at least half of the lectures according to the semester schedule.
-
ELKRM17308 6 credits
Data Mining Techniques
Module aim
To provide knowledge about data mining methods used to reveal objectively existing patterns into various nature datasets, to develop the ability to select and apply the suitable data mining method for particular task.
Module description
Module content is focused on modern data mining techniques and their application to find previously unknown and potentially useful information analysing big data sets. Module content includes: data preprocessing and exploratory data analysis, classification methods (nearest neighbour’s method, naive Bayes classifier and decision trees), regression analysis, data clustering and evaluation of model performance.
Students must participate in no less than 80% of the scheduled practical works
Free choice
Free choice
4 Semester
obligatory
-
ELEIM17451 30 credits
Master Graduation Thesis
Module aim
Perform research in the application field of automatic systems engineering, summarize research results and prepare technical report of Graduation Work demonstrating abilities to integrate knowledge acquired during studies, and work individually or in team, and by successful defence of Master’s Graduation Work proof achievement of goals of study program.
Module description
Theoretical and experimental research completion and summation. The research result presentation at scientific conference, Master Thesis report preparation and public defence.
The problem, aim, tasks, result and significance of the research are presented in the final work. Adequate conclusions and further recommendations are deduced and defended.
obligatory
-
ELEIM17451 30 credits
Master Graduation Thesis
Module aim
Perform research in the application field of automatic systems engineering, summarize research results and prepare technical report of Graduation Work demonstrating abilities to integrate knowledge acquired during studies, and work individually or in team, and by successful defence of Master’s Graduation Work proof achievement of goals of study program.
Module description
Theoretical and experimental research completion and summation. The research result presentation at scientific conference, Master Thesis report preparation and public defence.
The problem, aim, tasks, result and significance of the research are presented in the final work. Adequate conclusions and further recommendations are deduced and defended.
Statistics
| Metric | Value |
|---|---|
| Enrolled students | 8 |
| Enrolled to FT | 8 |
| Min FT grade | 8.89 |