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DESCRIPTION OF THE COURSE

Name of the course:

Automatic control systems

Code: MESCS01 Semester: 1

Type of teaching:

Lectures (L)

Laboratory work (Lab.)

Lessons per week:

L – 2 hours

Lab. – 2 hours

Number of credits 5

LECTURER:

Assoc. prof. Alexandar Ichtev PhD (FA) – tel.: 965 2420, еmail: [email protected]

Assoc. prof. Tsonio Slavov PhD (FA) – tel.: 965 2420, еmail: [email protected]

Assoc. prof. Teofana Puleva PhD (FA) – tel.: 965 2526, еmail: [email protected]

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM:

Compulsory for the regulat students speciality ”Systems for energy saving control”, MEng

programme, Faculty of Automation, Technical University of Sofia.

AIMS AND OBJECTIVES OF THE COURSE:

Automatic control systems gives theoretical background for investigation of continuous linear as

well as discrete control feedback control systems analysis and design. Particular problems for

analysis and control are investigated.

DESCRIPTION OF THE COURSE:

The main topics concern: Systems and control. Mathematical models of linear control systems:

differential equations, transfer functions, block diagrams, block diagram transformations. Control

systems’ characteristics. Stability of linear control systems. Control systems’ performance. Control

systems’ synthesis in frequency domain. State-space analysis of linear dynamical systems;

Canonical forms representation, Controllability and Observability of linear systems; Discrete-time

systems; z-transform method; Transfer functions and state-space models for discrete-time systems;

Stability of linear discrete-time systems; Pole placement design; Estimator design; Optimal control;

H∞ controller.

PREREQUISITES:

Mathematics I, II and III, Electrical Engineering Theory I and II

TEACHING METHODS:

Lectures, using slides. Laboratory work applying computer systems MATLAB and SIMULINK

with reports, prepared by the students and examined by the teacher

METHOD OF ASSESSMENT:

Written final examination (80%); laboratory work (20%).

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY:

1. Ishtev, K. „Automatic control theory“. Technical University - Sofia, 2007, ISBN 978-954-438- 641-

2. 2.

2. Ichtev, A., T. Puleva. „Control theory (part one) – laboratory manual“ . Technical University – Sofia,

2005, ISBN 954-438-523-1. 3. Ichtev, A.,. „Automated regulator theory – proble m collection (theory, solved examples, problems)

Technical University – Sofia, 2006, ISBN-10:954-438-549-5, ISBN-13: 978-954-438-549-1. 4. Linear Control Systems Engineering Methods, 2004 Technical University of Sofia (in Bulgarian); 5. G. Franklin, J. D. Powell, A. Emami-Naeini (2005), Feedback control of dynamic systems, 5th

Edition, ISBN 0-131499300; 6. B. Kuo, F. Golnaraghi (2002), Automatic Control Systems, Prentice-Hall International, Inc, 8th

Edition, ISBN 10-0471134767.


Name of the course:

Computer Technologies for System

Identification and Adaptive Control

Code MESCS 02

Semester: I

Type of teaching:

Lectures,

Laboratory work

Lessons per week:

L – 2 hours

LW – 2 hours

Number of Credits: 5

LECTURER:

Prof. Emil Garipov, PhD. (FA) – tel.: 965 3459, email: [email protected],


Assoc. Prof. Tsonyo Slavov, PhD. (FA) – tel.: 965 2420, email: [email protected],


COURSE STATUS IN THE CURRICULUM: Mandatory for all students in the Power

Save Control MEng programme of the Faculty of Automation at the Technical University of

Sofia.

AIMS AND OBJECTIVES OF THE COURSE: Students are introduced to software and

hardware tools for application of general methods for mathematical model design based on

the input/output plant signals.

DISCRIPTIONS OF THE COURSE: Classical problems for dynamic system identification

by nonparametric models using deterministic and stochastic test signals are examined. The

graphical techniques and applied optimization procedures are studied in order to transform

these transient models into the well-known continuous transfer function. Another main course

stream is identification by discrete regressive models. The problems of the off-line and on-

line linear and non-linear parameter estimation via the standard least squares method and its

modifications in open- and closed-loop control system are treated. Attention is paid on the

estimation quantity as unbiased and consistent estimates, and answers are given about the way

how to provide these features. The choice problems of appropriate model structure and good

experiment conditions are discussed and the criteria to validate the estimated models are

described. The recursive methods for estimation of time-varying plant parameters are

examined. The general concepts of adaptive control are introduced. Algorithms for both self-

tuned controllers and multiple model controllers are studied.

PREREQUISITES: Control Theory.

TEACHING METHODS: Lectures supported by Power Point present the theoretical part of

the course. Laboratory works use the program environment MATLAB/SIMULINK, incl. the

libraries System Identification Toolbox, Optimization Toolbox, Control System Toolbox and

own program functions, in order to measure and process the real-time and simulating input-

output data from the examined plants. There are 4 written home works.

METHOD OF ASSESSMENT: Written final examination (70%), laboratory reports defence

(20%), and homework assignments (10%).

INSTRUCTION LANGUAGE: Bulgarian.

BIBLIOGRAPHY:

1.Garipov, Е. System Identification (third ed.) – vol. I and II, TU-Sofia, 2007 (in Bulgarian).

2. Garipov, Е., Tc. Slavov. Textbook of System Identification Laboratory Works, TU-Sofia,

2009 (in Bulgarian).

3. Garipov, Е. Solved Problems for Control Systems Design using MATLAB/SIMULINK,

TU-Sofia, 1997, 1999 (in Bulgarian).

4. Ljung, L. System Identification: Theory for the User (second ed.). Prentice Hall, 1999.


Name of the course:

Communication networks and standards in industry Code: MESCS 03 Semester: 1

Type of teaching:

Lectures (L)


Lessons per week:

L – 2 hours

Lab. – 2 hours

Number of credits 5

LECTURER:

Assoc.Prof. Metody Georgiev (FA) tel: 0895586162, e-mail: [email protected]


Assoc.Prof. Vasil Galabov (FA), tel: 0882142502, e-mail: [email protected]



Compulsory for the students speciality Automation, Information and Control Engineering, MEng

Programme in “Systems for energy efficient control”, Faculty of Automation.


To give knowledge on the solving problems in design, development and analyses of industrial

communication systems in industry and energy concerning the international and regional standards.


Main topics of the course are the international standards for industrial communications including

Open PLC, OPC DA, OPC UA, IEC61850, IEC60870-140, etc. The design and analyses of

industrial communication systems, redundant systems for communication and interoperability

between different communication systems are presented in the course. SCADA systems and

industrial data archiving function are covered by the course material.

PREREQUISITES:

Windows, MS SQL Server, XML, PLC and Windows based software design

TEACHING METHODS:

Lectures, laboratory work from laboratory manual, work in teams, protocols preparation and

defence.


Written final examination.


BIBLIOGRAPHY:

1. Доц. д-р Георги Сапунджиев, Информационни системи в индустрията, ТУ – София,

2005

2. Доц.д-р Станчо Джиев, Индустриални мрежи за комуникация и управление, ТУ-

София, 2003

3. Wolfgang Mahnke, Stefan-Helmut Leitner, Matthias Damm, OPC Unified Architecture,

Springer; 2009

4. Knapp Eric, Industrial Network Security: Securing Critical Infrastructure Networks for

Smart Grid, SCADA, and Other Industrial Control Systems,Syngress,2011

5. Frederick Meier, Clifford Meier,Instrumentation And Control Systems Documentation,

Instrumentation Systems, 2011

6. Кузьмин И.В., В.А. Кедрус, Основы теории информация и кодирования, Киев, Вища

школа, 1997.

7. Burch J., G.Grudnitski, Information systems. Theory and practice, New York, Acad.

J.Wiley&Sohn, 1997.

mailto:[email protected]


Name of the course:

Modelling of Technical and Economic Systems

Code: MESCS 04 Semester: I

Type of teaching:

Lectures (L)


Lessons per week:

L – 2 hours

Lab. – 2 hours

Number of credits 5

LECTURER:

Assoc prof. A. Efremov (FA) - tel. 0896861315, [email protected]



Eligible course for students from speciality: Automation, Information and Control Engineering,

Meng programme, Faculty of Automation.


To give knowledge on data driven modelling, also named system identification and its application

in technics, energy, retail, finance and other sectors of economics. The topic about marketing

strategy optimization is also covered.


The quantity of data, possessed by the humanity grows exponentially. This leads to a fast evolution

of data driven modelling. The need of experts who are able to design data mining solutions for

particular businesses, to develop algorithms, to construct auto-modelling workflows, etc. also grows

exponentially. The system dynamics is frequently neglected, which gives the opportunity the

engineers from TU – Sofia to become highly evaluated experts. The optimization is the fundament

of data driven modelling and decision making systems. For this reason in the second part of the

course the linear and non-linear programming are covered. The non-linear programming is used

when develop non-linear models. Special attention is paid on marketing strategy optimization

workflows, where methods from machine learning and linear programming are used.

PREREQUISITES:

Linear Algebra and Analytic Geometry, Mathematical Analysis, Statistics.

TEACHING METHODS:

Lectures and practical work during lab. exercises.


Exam (written) at the end of the course.


BIBLIOGRAPHY: 1. A. Efremov. Multivariable System Identification. Dar-RH, 2014, ISBN 978-954-9489-42-2.

2. Е. Garipov. System Identification. Part II. Identification by Discrete. Stochastic Regression Models. TU –

Sofia, 2004.

3. S. Stoyanov. Production Processes Optimization. Tehnika, Sofia, 2003, ISBN 954-030256-0.

4. Т. Petkov. System Identification. Tehnika, Sofia, 1984.

5. J. Nocedal, S. Wright. Numerical Optimization. Springer, 2006. ISBN-10: 0-378-30303-0.

6. J. Rawlings, S. Pantula, D. Dickey. Applied Regression Analysis: A Research Tool. Springer, 1998.

7. B. D. Bunday. Basic Optimization Methods. Hodder Arnold, London, U.K.: E.J.Arnold, 1984.

8. D. Hosmer, S. Lemeshow. Applied Logistic Regression. Wiley Series in Probability and Statistics. John

Wiley & Sons, Inc., 2000. ISBN 0-471-35632-8.

9. O. Nelles. Nonlinear System Identification. From Classical Approaches to Neural Networks and Fuzzy

Models. Springer-Verlag, Berlin, Heidelberg, 2001.



Name of the course:

Converters in Electromechanical Systems

and Electric Drives Automation


Type of teaching:

Lectures, laboratory work, course work

Lessons per week:

L – 2 hours

LW – 2 hours

Number of credits: 5

LECTURER: Assoc. Prof. Ph.D. Eng. Evtim I. Ionchev (FA) – tel: 965 2948, email: [email protected]


COURSE STATUS IN THE CURRICULUM: Obligatory optional for the students specialty

Energy Efficient Control Systems, M.Sc. programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: Students acquire the knowledge needed for the

conversion of electric energy and process control in semiconductor converters. Functional design

of power semiconductor converters, skills for experimental research in this area.

DESCRIPTION OF THE COURSE: Consistently present: principles of operation; circuit design;

mathematical description; control algorithms in the respective modes; Structural schemes; dynamic,

static and energetic characteristics of the systems under consideration management methods. The

course combines training problem with giving specific knowledge. When considering a comparative

analysis of relevant principles, circuits and control algorithms, which allows to assess the

possibilities of the studied systems for practical applications in various fields.

PREREQUISITES: Knowledge on the fields of “Mathematics”, “Physics”, “Electro-techniques”,

“Semiconductor devices”, “Pulse and digital techniques”, ”Electrical Measurement”,

“Electromechanical devices”, “Control theory”.

TEACHING METHODS: Lectures assisted with multimedia; laboratory works on physical and

computer modeling. Materials about the lectures and laboratory works are handed up to students.

METHOD OF ASSESSMENT: Continuous assessment based on two tests.


BIBLIOGRAPHY: 1. Lecture notes; 2.Rashid, Muhammad H., Power Electronics Handbook,

Academic press, 2001., 3. Peter Vas, Sensorless vector and direct torque control, Oxford university

press,2004, 4. Эпштейн И.И., Автоматизированный электропривод переменного тока,

Энергоиздат, М., 2002. 5. Benjamin C.Kuo, Automatic control systems, 2005, 6. Шрейнер Р.Т.,

Математическое моделирование электроприводов переменного тока с полупроводниковыми

преобразователями частоты, УРО РАН, 2000.


Name of the course:

Renewable energy sources and energy

saving electric drives


Type of teaching:

Lectures, laboratory work

Lessons per week:

L – 2 hours

LW – 2 hours


LECTURER: Prof. Ph.D. Eng. Todor S. Ionkov (FA) – tel: 965 2950, email: [email protected]

Assoc. Prof. Ph.D. Eng. Evtim I. Ionchev (FA) – tel: 965 2948, email: [email protected]

Ass. Prof. Ph.D. Eng. Docho T. Tsankov (FA) – tel: 965 2948, email: [email protected]


COURSE STATUS IN THE CURRICULUM: Obligatory optional for the students specialty


AIMS AND OBJECTIVES OF THE COURSE: The main objective of the course is to broaden

and deepen students' knowledge in the field of advanced systems with renewable energy sources

and energy-saving specialized control of electric drives.

DESCRIPTION OF THE COURSE: The course presents the basic types of renewable sources are

either not taught or presented in a limited volume in the respective disciplines of the academic

degree "Bachelor." Management systems for electric drives are examined in terms of opportunities

for recovery and energy savings. The typical electric drives are characteristic of electric transport,

wind and water power. Autonomy regimes are studied taking into account the characteristics of the

accumulated modules.

PREREQUISITES: Knowledge on the fields of “Mathematics”, “Physics”, “Electro-techniques”,

“Semiconductor devices”, ”Electrical Measurement”, “Control theory”.

TEACHING METHODS: Lectures assisted with multimedia; laboratory works on physical and

computer modeling. Materials about the lectures and laboratory works are handed up to students.

METHOD OF ASSESSMENT: Continuous assessment based on two tests.


BIBLIOGRAPHY: 1. Ключев В.И., Теория электропривода, Москва, Энергоатомиздат, 2001.

2. Ильинский Н.Ф. Основы электропривода ,Москва, Издательство МЭИ ,2003, 3. Ильинский

Н.Ф. и др. Общий курс электропривода, Москва, Энергоатомиздат 1992, 4. Копылов И.П.

Электрические машины, Москва, Высшая школа, 2004, 5. Charles L. Phillips, Feedback control

systems, New Jersey 2001, 6.Leonhard, W. Control of electrical drives, Berlin 1996, 7. Irving M.

Cottlteb, Power Supplies Switching Regulators, inverters end Converters (1994) New York, 8.

BURNS, R. S. Advanced Control Engineering (2001).



Name of the course:

Measurement of technological quantities,

metrology and quality control


Type of teaching:

Course project

Lessons per week:

CP – 2 hours

Number of credits 1

LECTURER:

Assoc. Prof. G. Milushev (FA) - tel. 029652380, e-mail: [email protected],



Course project for students of specialty “Energy saving control systems”, MEng

programme, Faculty of Automation.


The aim of the course project is to give ability and knowledge about measurements of technological

quantities.


In the suggested themes the students decides concrete task about metrological assurance and quality

control.

PREREQUISITES:

Basic knowledge: Mathematics, Physics, Electrical measurements, Measurements of non-electrical

quantities, Quality control

TEACHING METHODS:

Consulting.


Defense of course project.


BIBLIOGRAPHY: 1. Под ред. на Радев Х. Метрология и измервателна техника, Том 1, Софттрейд, София, 2010;

2. Радев Х., В. Богев. Неопределеност на резултата от измерването. С., Софтрейд, 2001;

3. Чаушев П. Метрология. С., ТУ-София, 1996;

4. Колев Н., П. Чаушев, В. Гавраилов. Основи на метрологичното осигуряване. С., Техника, 1982;

5. Euramet, July 2008, Metrology – in Short, 3rd Edition;

6. EAL Publication reference EA-4/02. Expression of Uncertainty of Measurement in Calibration

(including supplement 1 to EA-4/02);

7. JCGM 200:2012 International vocabulary of metrology – Basic and general concepts and associated

terms (VIM) 3rd edition 2008 version with minor corrections;



Name of the course

Robust Energy Saving Control of

Plants and Systems


Type of teaching:

Lectures and laboratory work

Course project

Lessons per week:

L – 2 hours; LW – 2 hours

CP – 0 hour


LECTURER:

Prof. D.Sc. E. Nikolov (FA) - tel.: 965 3417, еmail: [email protected]

Assoc. Prof. PhD Nina G. Nikolova (FA) - tel.: 965 2527; еmail: [email protected],

Assoc. Prof. PhD Vessela Karlova (FA) - tel.: 965 3941; еmail: [email protected]

Assoc. Prof. PhD Stanislav Enev (FA) - tel.: 965 3941; еmail: [email protected]


COURSE STATUS IN THE CURRICULUM: Compulsory for the students specialty “Energy

Saving Control System” of the Faculty of Automation “master”

AIMS AND OBJECTIVES OF THE COURSE: At the end of the course students are expected to

be able to apply: robust control, repetitive control, generalized fractional calculus, operators of

integration and derivation fractional, root locus and QFT-method of control system synthesis;

engineering and robust analysis.

DESCRIPTION OF THE COURSE: Below are the theoretical foundations of theory of robust-,

repetitive-, and QFT-control, integral transformations, generalized fractional calculus and their

applications in industrial control systems

PREREQUISITES: Control Theory, Control Instrumentation, Industrial Automation, Logic

Control, Multivariable Systems, Application Method Control, QFT-design of referent context

program 5.2.

TEACHING METHODS: Lectures, using slides, case studies, laboratory and course work, work in

teams, protocols and course work description preparation and defense.

METHOD OF ASSESSMENT: Two one-hour assessments at mid and end of semester (62%),

laboratories (18%), course work - two off assignments (20%)


BIBLIOGRAPHY: Николов Е. (2003), Приложни методи за управление на процеси I ч. (честотни методи и

системи с робастни свойства), ТУСофия; Николов Е. (2005), Робастни системи (приложни

методи за управление на технологични процеси - II ч.), ТУСофия; Николов Е. (2010),

Робастно Фрактално Управление (предиктивни и алгебрични методи; системи с разпределени

параметри), ТУСофия; Николов Е. (2004), Фрактални алгоритми и режекторни регулатори,

София 2004, ТУСофия; Николов Е. (2004), Специални математически функции и фрактални

оператори (справочно пособие), ТУСофия; Николова Н., E. Николов (2009), Приложни

методи за управление на технологични процеси, ръководство за лабораторни упражнения,

ТУСофия; Николова Н., E. Николов (2006), Методи и алгоритми за настройка на регу-

латори в системи за управление - Справочно пособие по дисциплината Приложни Методи за

Управление на Технологични Процеси ТУСофия; Карлова-Сергиева В. (2013), Проектиране

на системи за управление с гарантирано качество, Радикс ООД; Nikolov Е., D. Jolly, N.

Nikolova, B. Benova (2005), Commande Robuste, Sofia 2005, Nikolov E., S. Enev (2009),

Asservissement et Régulation Continue, Publ. House of TU-Sofia,; Oustaloup A. (1991), La

commande CRONE (commande robuste d’ordre non entier), Hermès, Paris; Oustaloup A.

(1996), La dérivation non entière (théorie, synthèse et applications), Hermès, Paris.




Name of the course:

Intelligent energy-efficient control and processing

of information


Type of teaching:

Lectures (L)


Lessons per week:

L – 2 hours

Lab. – 2 hours

Number of credits 5

LECTURER:

Prof. Ph.D. Snejana Yordanova (FA) - tel.: 965 3313, email: [email protected]



Compulsory for the students from speciality Systems for Energy-Efficient Control, MEng

programme, Faculty of Automation.


The students receive knowledge and skills on the principles and the methods for energy-efficient

control and processing of information based on fuzzy logic, neural networks and evolutionary

algorithms as well as on their application for: control of high energy consuming plants with variable

parameters, inertia and model uncertainty; processing of measurement and linguistic information

for decision making; expert systems; classification, optimization, modelling and prediction.


Main topics: Introduction to intelligent control systems; Artificial neural networks neural models

controllers and predictors; Fuzzy sets and fuzzy logic, fuzzy models and controllers – Mamdani,

Sugeno, parallel distributed compensation; Neuro-fuzzy systems – clustering analysis,

classification, structure identification; neuro-fuzzy control and prediction; Evolutionary computing;

Expert systems, Intelligent agents. In the laboratory exercises intelligent energy-efficient

approaches to control, modelling and prediction are illustrated on pilot models of real systems –

dryer, heat-ventilation and air-conditioner, drum boiler, hydraulic system, etc.

PREREQUISITES:

Control Systems, Computer based technologies for identification and adaptive control systems

TEACHING METHODS:

Lectures, laboratory work from laboratory manual, work in teams, protocols preparation and

defence.


Two written exams in the middle and at the end of the semester (80%); laboratory work (20%).


BIBLIOGRAPHY: 1. Йорданова С. Методи за синтез на размити регулатори за робастно управление на процеси,

КИНГ, С., 2011.

2. Младенов В., С. Йорданова. Размито управление и невронни мрежи. ТУ-София, София, 2006, 168.

3. Ross T.J. Fuzzy Logic with Engineering Applications. McGraw Hill, Inc., 1995.

4. Jantzen J. Foundations of Fuzzy Control, John Wiley & Sons Inc. 2007.

5. Tanaka K., Hua O. Wang. Fuzzy Control Systems Design and Analysis, John Wiley & Sons Inc., 2001

6. Jang J.-S.R., C.-T.Sun, E. Mizutani. Neuro-Fuzzy and Soft Computing. A Computational Approach to

Learning and Machine Intelligence. Matlab Curriculum Series. Prentice-Hall, Inc., N.J. 07458, 1997.

7. Haupt R.L. and S. El. Haupt. Practical Genetic Algorithms, NY, John Wiley & Sons, 1998

8. IEC 61131–Programmable Controllers, 1999.

9. Йорданова С., М.Георгиев, Д.Меразчиев, В.Янков. Интелигентни системи за управление.

Ръководство за лабораторни упражнения, С., Изд.ТУ-София, 2014.


Name of the course:

Energy-saving control in electromechanics

and building automation


Type of teaching:

Lectures, Laboratory work

Lessons per week:

L – 2 hours

LW – 2 hours


LECTURER: Prof. Ph.D. Eng. Todor S. Ionkov (FA) – tel: 965 2950, email:[email protected]


COURSE STATUS ON THE CURRICULUM: Obligatory optional for the students specialty


AIMS AND OBJECTIVES OF THE COURSE: The aim of the course "Energy-saving control in

electromechanics and building automation" is to expand students' theoretical knowledge in the

process of electromechanical energy conversion discussed on the basis of the generalized electric

machine with widespread use of the automatic control theory.

DESCRIPTION OF THE COURSE: The problems related to the optimal control of energy-

efficient systems for heating, ventilation and air conditioning on the class of optimal supervisory

control in its different varieties, and methods for generating the optimal definition rules in these

systems. Laboratory exercises illustrate and complement the lectures. Performed on stands with real

acting electromechanical and building systems, which contributes to increasing the level of

knowledge and practical skills of the students. To obtain more information, some of the studied

systems are examined by modeling and computer simulation.

PREREQUISITES: The course is based on “Higher Mathematics”, “Physics”, “theoretical

electrotechnics”, “Automatic Control theory”, “Electromechanical devices”, “Control of

electromechanical systems”.

TEACHING METHODS: Lectures, Laboratory works on physical and computerised models and

course work for every student. Written materials on the laboratory works are handed up to the

students.

METHOD OF ASSESSMENT: Written exam.


BIBLIOGRAPHY: 1. Ключев В.И., Теория на електрозадвижването, С., Техника, 1986, 2.

Илинский Н.Ф. Основы электропривода ,Москва, Издательство МЭИ,2003. 3. Charles L.

Phillips, Feedbsck control systems, New Jersy 2001 4. Per-Goran Person, William Morton, Control

Handbook HVAC Systems, Malmo, Sweden,1994, 5. Волов Г.Я., Моделирование работы систем

отопления, вентиляции и теплоснабжения – теоретические основы, Минск, Энерговент, 2007,

6.John Levenhagen, HVAC Control System Design Diagrams, McGraw Hill, ISBN 0-07-038129-1,

1998. 7. Shengwei Wang, Intelligent Buildings and Building Automation, Routledge, ISBN-10:

04115475708, 2009


Name of the course

Energy Efficient Robots


Type of teaching:

Lectures and laboratory work,

Lessons per week:

L – 2 hours; LW – 2

hours


LECTURERS:

Assoc. Prof. Ph. D. Vladimir Zamanov, phone 965-2637, email: [email protected],

Assoc. Prof. Ph. D. Vassil Balavessov , phone 965 3073, еmail: [email protected],

Assoc. Prof. Ph. D. Ivan Avramov , phone 965-3991, email: [email protected],


COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Energy

efficient control systems of the Faculty of Automation, MEng programme.

AIMS AND OBJECTIVES OF THE COURSE: The aim of the course is to give basic

knowledge to the students of the design principles and methods of energy efficient systems of

manipulation and mobile robots, as well as obtaining practical skills in solving engineering

problems.

DESCRIPTION OF THE COURSE: The course is structured into three thematically related

training modules, thereby focusing on the functional unity of the mechanical, the energy and

the information robot subsystems, and thus representing a good basis for the implementation

of the mechatronic approach to the design. Main topics: planning of smooth trajectories for

robots in joint and Cartesian coordinate, planning of efficient motions of mobile robots,

kinematic control of robots with energy minimization, dynamic description and control of

robots, analysis of the main energy dissipation in actuators and mechanisms, mechanical

energy storage, statically and dynamically balanced robots, energy-efficient balancers,

modeling, simulation and computer analysis of basic robotic characteristics, evaluation of the

energetical efficacy of robotic technologies.

PREREQUISITES: Mathematics, Physics

TEACHING METHODS: Lectures, case studies, laboratory work.

METHOD OF ASSESSMENT: exam


BIBLIOGRAPHY: Заманов В., Карастоянов Д., Сотиров З., Механика и управление на

роботите, Литерапринт, София, 1993.; Siciliano, B., Sciavicco, L., Villani, L., Oriolo, G., Robotics:

Modelling, Planning and Control, ISBN 978-1-84628-641-4, 2009 Springer-Verlag London

Limited.;Заманов В., Мобилни роботи. Локомоционни системи. Издателство ТУ-София,

София, 2012.; Заманов В., П. Венков, Мобилни роботи.Сензори. Издателство ТУ-София,

София, 2013.; 2013.; Craig, J. J, Introduction to Robotics: Mechanics & Control, ISBN:

8131718360, Pearson Prentice Hall, Upper Saddle River, NJ, 3rd ed., 2008.; Павлов В.

Проектиране на роботи, Изд. ТУ-София, 1991.; Гълъбов В. Синтез на механизми в

роботиката, Изд. ТУ-София, 1990; Корендясев А. И., Манипуляционные системы роботов,

Машиностроение, Москва, 1989.


http://tu-sofia.bg/eng_new/Fakulteti/faculties/fksu/fksu-menu.php


Name of the course:

Computer Control Systems


Type of teaching:

Lectures (L)


Lessons per week:

L – 2 hours

Lab. – 2 hours

Number of credits 5

LECTURER: Assoc. Prof. Ivan Evgeniev Ivanov, tel. 965 20 41, email: [email protected]

Assoc. Prof. Georgi Rouzhekov, PhD, tel. 965 2456, [email protected] Technical University of Sofia


Compulsory for the students of Energy Saving Control Systems, MEng programme, Faculty of

Automation.


This course introduces advanced knowledge on computer architectures oriented mainly to computer

control systems.

DESCRIPTION OF THE COURSE: The main topics concern: Architecture of microcomputer

systems; Organization and architecture of computer control systems (CCS): systems architecture,

software and hardware design of CCS, “human-machine” interface, real-time operating

environment; embedded and stand-alone controllers, PLCs. The main goal of the course is design

aspects of microcomputer systems oriented to control applications. Design and exploitation of

applications oriented to different domains is discussed either. Hardware influences on system and

application software is special issue of the course.

PREREQUISITES:

Programming, Computer Architectures, Microelectronics, Numerical Devices

TEACHING METHODS:

Lectures, laboratory work from laboratory manual, work in teams, report defense

METHOD OF ASSESSMENT: Written final examination


BIBLIOGRAPHY:

1. ABB, IEC61131Control Languages, 2001

2. Jonathan Love, Process Automation Handbook, A Guide to Theory and Practice, Springer, 2007

3. Frank D. Petruzella, Programmable Logic Controllers, McGraw-Hill, 2005

4. Hugh Jack, Automating Manufacturing System with PLC, 2007

5. IDC Technologies, Process Control, Automation, Instrumentation and SCADA, 2012

6. Myke King, Process Control: A Practical Approach, John Wiley & Sons Ltd, 2011

7. T. Noergaard, Embedded Systems Architecture, Second Edition: A Comprehensive Guide for Engineers

and Programmers, Newnes; 2 edition (December 28, 2012)

8. Ed Lipiansky, Embedded Systems Hardware for Software Engineers, McGraw-Hill Professional; 1

edition (November 22, 2011)


Name of the course:

Process Control in Power Engineering


Type of teaching:

Lectures (L)


Lessons per week:

L – 2 hours

Lab. – 1 hours

Number of credits 4

LECTURER: Assoc. Prof. Teofana Puleva, PhD, tel. 965 25 26, email: [email protected]

Assoc. Prof. Andrey Yonchev, PhD, tel. 965 2452, [email protected], Technical University of Sofia


Compulsory for the students speciality Energy Saving Control Systems, Meng programme, Faculty

of Automation.


To give knowledge on the advanced methods for analysis and design of control systems in power

engineering, more precisely in control system design for renewable energy sources (RES)

modelling and design. The course concern hydro- and wind turbine advanced control algorithms, as

well as decision making analysis for energy sources optimal control.

DESCRIPTION OF THE COURSE: The main topics concern: system modelling in power

engineering, models of hydraulic and wind energy conversion system, mathematical models based

on balanced equations, application of improved control algorithms in hydro power engineering:

load disturbance rejection algorithms, water column compensation algorithms, adaptive and

multiple model adaptive control algorithms, gain scheduling control and internal model control, as

well as adaptive and robust control algorithms for wind turbine generator power control. The

specific features of power control in energy grids with substantial part of RES will be studied. The

application of model predictive control is considered in some control tasks in power engineering.

The decision making analysis for energy sources optimal control is focused on the Markovian

decision process application. The laboratory work illustrates the analysis and design of advanced

control algorithms for complex technological processes in power engineering. Program language –

MATLAB.

PREREQUISITES:

Mathematics, Electric drive systems, Theoretical Electrotechnics I, II, Control Theory

TEACHING METHODS:

Lectures, laboratory work from laboratory manual, work in teams, report defense


Written final examination (80%); laboratory work (20%).


BIBLIOGRAPHY:

1. Kundur P.(1994) , Power system stability and control, McGraw-Hill, Inc.

2. Нанчев, С. (1992), Основи на автоматизацията на електроенергийните системи, Техника, София.

3. Egeland, O., J. Gravdahl (2002). Modeling and Simulation for Automatic Control, T. Gravdahl,. Marine

Cybernetics AS, Trondheim, ISBN 82-92356-01-0, 1st. edition.

4. Astrom K.,B. Wittenmark. Adaptive control (2008). 2nd Edition. Dover Publ., New York, 2008.

5. Munteanu, I., A. Bratcu, N. Cutululis, E. Ceanga, (2008). Optimal Control of Wind Energy Systems,

Springer, ISBN 978-1-84800-079-7.

6. J. A. Rossiter J. A., Model Based Predictive Control, A Practical Approach, CRC PRESSS, 2010.



Name of the course:

Computer modeling, synthesis and optimization of

electro technical systems and devices

Code: MESCS14 Semester: 1I

Type of teaching:

Course project

Lessons per week:

Number of credits 1

LECTURER:

Assoc. prof. Ilona Iatcheva PhD (FA) – tel.: 965 3389, еmail: [email protected]

Ass. prof. Nikolina Petkova PhD (FA) – tel.: 965 2498, еmail: [email protected]



Compulsory for the regulat students speciality ”Systems for energy saving control”, MEng

programme, Faculty of Automation, Technical University of Sofia.


"Computer modeling, synthesis and optimization of electrotechnical systems and devices" gives

theoretical background and familiarizes students with possibilities for computer modeling, synthesis

and optimization of electromagnetic systems and devices in order to increase the efficiency and

reliable operation ff the system.


The work on the project is related to modeling of processes in different electromagnetic systems

and circuits. The precise analysis of the processes is carried out using advanced numerical methods

and software: OrCAD PSpice (analysis of electric and electronic circuits) and Matlab, FEMM and

QuickField (for field analysis of electromagnetic devices using finite elements method). Objects of

investigation and modeling are: 1) electromagnetic processes in electrotechnical devices for which

are determine a wide range of integral characteristics such as inductances, capacity, energy, forces,

moments; 2) modeling of processes in nonlinear circuits, spectral analysis, Fourier analysis of

discrete signals and systems. Using the relevant software is carried out computer simulation of

processes in specify constructive and regime parameters of the studied electromagnetic system.

Based on analysis of results are selected constructive and regime parameters, which change

significantly affect current processes and then numerical experiments have to be carried out for

different their values. The optimal values of the selected parameters are determined in order to

improve the effectiveness of the device or system.

PREREQUISITES:

Mathematics I, II and III, Electrical Engineering Theory I and II

TEACHING METHODS:

Consultations and self-study


Final assessment is formed on the basis of written report and presentation.


BIBLIOGRAPHY: 1. 1. Brandisky K. Zh.Georgiev, V. Mladenov, R.Stancheva, Textbook of Theoretical Electrical

Engineering, Part II, KING Publishing, 2005.

2. Brandisky K. and I.Yacheva, CAD systems in electromagnetism, SIELA, 2002.

3. James R.Glaycom, “Applied Electromagnetics using QuickField and Matlab”, Infinity Science Press

LLC, 2008

4. Brandisky K, V. Mladenov, D. Valchev, " Solved problems in Electrical Engineering with MATLAB ",

TU - Sofia, 2000, 2010, Sofia

5. Brandisky K., V. Mladenov, S. Petrakieva, "Manuel for solving problems in Theoretical Electrical

Engineering using PSPICE, KING 2012, Sofia

description of the course - tu-sofia.bgoldweb.tu-sofia.bg/eng_new/ects/ectas/ectas12-13/... · ......

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