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List OS4 (BAICE43–EСТК 5)

L4O1 Digital Control Systems

L4O2 Analogue Electronic Measurement Instruments

L4O3 Automation of Manufacturing Mechanisms

L4O4 Process Modelling and Optimization

L4O5 Biotechnological Measurements

L4O6 Artificial Intelligence



DISCRIPTION OF THE COURSE





Name of the course:

Digital Control Systems

Code: BAICE43


Semester: 7

Type of teaching:

Lectures, Laboratory work,

Course work

Lessons per week:

L –2 hours,

LW – 1.5 hours

Number of Credits: 5


LECTURER:

Assoc. Prof. Emil Garipov PhD. (FA) – tel.: 965 3459, email: emgar@tu-sofia.bg ,

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: Students, which are familiar with the bases of the control theory, have to study the main design digital controller methods and extend their knowledge into the investigation of digital control systems.

DISCRIPTIONS OF THE COURSE: The lectures cover the tuning and implementation of digital controllers after parameter optimization (PID controllers in various modification forms, unified PID), Dahlin compensators, Kalman, Isermann and own-type dead-beat controllers, modal controllers, minimum variance controllers, linear quadratic controllers, predictive controllers, etc. The numerical complexity of the teaching design methods is examined and the presented algorithms properties and characteristics depending on the different dynamic plants are drawn. The students study the practical aspects of digital control systems operation in a condition of noise, time varying point sets, errors after discretization, wind up effect, control signal constraints, etc.

PREREQUISITES: Control Theory, System Identification, Control Theory, Systems and Processes Modelling and Simulation.

TEACHING METHODS: Lectures supported by slides, laboratory works using the program environment MATLAB/SIMULINK and own program functions.

METHOD OF ASSESMENT: Written final examination with short time discussion (70%), laboratory report defence (20%), course works and personal defence (10%).

INSTRUCTION LANGUAGE: Bulgarian language.

BIBLIOGRAPHY: 1. Garipov, Е. Digital Control Systems – vol. I and II, TU-Sofia, 2004. 2. Velev, К. Adaptive systems, Sofia, 1995. 3. Astrom, K and T. Hagglund. PID Controllers (Sec. ed.). Instrument Society of America, 1995.

DESCRIPTION OF THE COURSE


Name of the course:

Analogue Electronic Measurement Instruments

Code: BAICE43

Semester: 7

Type of teaching:

Lectures,

Laboratory work

Lessons per week:

L – 2 hours;

LW – 1.5 hours

Number of credits: 5

LECTURER:

Assoc. Prof. Ph.D. E. Yankov (FA) – tel.: 965 33 83

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: The aim of the course is to provide contemporary knowledge on the principles and metrological analyses of analogue electronic measurement instruments.

DESCRIPTION OF THE COURSE: The course includes basic working principles, theory, schemes, design, metrological analyses of analogue electronic measurement instruments for electrical quantities – voltage, current, power, faze shift, power factor, frequency, time delay and their special blocks and components – instrumentation amplifiers, generators, transducers of electrical to electrical quantities.

PREREQUISITES: The course is based on Electrical Engineering Theory, Electric Measurements, Analogue Electronic Measurement Instruments.

TEACHING METHODS: lectures, laboratory work

METHOD OF ASSESSMENT: Written Exam

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY:

1. Станчев, И. Б. "Електронни аналогови средства за измерване", Издателство на ТУ, С., 1994 г. 2. Станчев, И. Б., И. А. Куртев, Д. А. Самоковлийски, И. Н. Иванов и Е. А. Янков "Електронни измервателни уреди (аналогови)", ръководство за лабораторни упражнения, Издателство на ВМЕИ, 1978 г.

DESCRIPTION OF THE COURSE


Name of the course:

Automation of Manufacturing Mechanisms


Code: BAICE43

Semester: 7

Type of teaching:

Lectures, Laboratory works and Course Work

Lessons per week:

L – 2 hours

LW – 1.5 hours


Number of credits: 5


LECTURER:

Assoc. Prof. Ph.D. Eng. Rumen Rainov (FA), Tel: 965-39-45, email: rrainov@tu-sofia.bg

Technical University of Sofia

COURSE STATUS ON THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: The aim is the students to be acquainted with the specific features of different manufacturing mechanisms, with concrete problems for their automation and specific drives and with the methods for their solving. Independent students’ activity on the discussed materials is stimulated.

DESCRIPTION OF THE COURSE: The course is developed problematically. It gives knowledge about typical requirements to the systems for drive and automation of the basic classes of manufacturing mechanisms; mathematical description of their main quantities and processes; it’s stressed on the specific for any class problems; possible solutions are systemised. For illustration of up to date solutions of concrete problems, typical circuits for blocks and devices are derived.

PREREQUISITES: The course is based on Electromechanical Devices, Measurement of Electric Quantities, Electromechanical Systems Control, and Systems for Control of Drives.

TEACHING METHODS: Thee forms are used: 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: A written exam in the end of VII semester is carried out.

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY: 1. Йорданов С., К.Кутрянски, Автоматиза­ция на производстве­ните механизми, С., Печатна база ТУ-София, 2001.; 2. Йорданов С., Автоматизация на производствените механизми, С., Печатна база ТУ-София, 1993.; 3. Йорданов С., Р.Райнов, Ръководство за лабораторни упражнения по Авто­матизация на производствените механизми, С., Печатна база ТУ-София, 1989. 4. Йорданов С., Г.Даскалов, Автоматизация на производствените механизми (изчисли­телни експерименти и оптимизация), Ръководство за лабораторни упражнения, Пловдив, Технически университет, 1991.

DESCRIPTION OF THE COURSE


Name of the course:

Process Modelling and Optimization

Code: BAICE43

Semester: 7

Type of teaching:

Lectures,

Laboratory work

Lessons per week:

L – 2 hours;

LW – 1.5 hours

Number of credits: 5

LECTURER:

Assoc. Prof. Ph.D. Stancho Djiev (FA) – tel.965-2298, email: djiev@tu-sofia.bg

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Compulsory for the students in the “Informational and Control Engineering” B.Sc. programme of the Department of Process Automation, Faculty of Automation."

AIMS AND OBJECTIVES OF THE COURSE: Introduce the classical methods for process statics and dynamics theoretical modelling as related to industrial process control systems. To give knowledge about the methods and practice of process optimization.

DESCRIPTION OF THE COURSE: The main topics include: process statics and dynamics theoretical modelling; modelling using the preservation principle; models of continuous processes using analogy; models of discrete processes; models of conveyor processing and assembly lines; criteria for single-variable optimization; methods for single-variable optimization - search and gradient methods; comparison of methods for single-variable optimization; criteria for multivariable optimization; methods for multivariable optimization - search and gradient methods; comparison of methods for multivariable optimization; optimization of multi-stage processes - dynamic programming; multi-criterial optimization methods.

PREREQUISITES: Physics, Technical Mechanics, Control Theory, Control Instrumentation, Systems Identification, Process Control Automation.

TEACHING METHODS: Lectures with slides, case studies, course work, laboratory work with laboratory manual, work in teams, protocols preparation and defence. .

METHOD OF ASSESSMENT: One three-hour examination at the end of semester (80%) plus laboratories (20%).

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY: 1.Джиев, Ст. Моделиране и оптимизация на процеси, ТУ, София, 2001. 2.Живков, Д., Моделиране и оптимизация на производствени процеси, ТУ, София, 1989. 3.Реклейтис, Г., А. Рейвиндран, К. Рагсдейл, Оптимизация в технике, М., Мир, 1986. (прев. англ.). 4.Вучков, И., С.Стоянов, Математическо моделиране и оптимизация на технологични обекти, С., Техника, 1986. 5.Стоянов, С., Оптимизация на технологични обекти, С., Техника, 1993. 6.Сотиров Г., С. Филипова, Дискретно събитийни системи - Методически указания за лабораторни упражнения. Изд. на ТУ-София .

DESCRIPTION OF THE COURSE


Name of the course:

Biotechnological Measurements

Code: BAICE43

Semester: 7

Type of teaching:

Lectures, Laboratory work,

Course work

Lessons per week:

L – 2 hours;

LW – 1.5 hours

Number of credits: 5

LECTURER:

Assoc. Prof. Ph.D. Dimitar Nenov (FA), tel.: 965 2596, email: nenov_dan@mail.bg

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: To teach the students the most important knowledge of the information and metrological assurance of the biotechnological processes with different methods and equipments for direct and indirect measurement of the variables and methods of data processing.

DESCRIPTION OF THE COURSE:

The aim of the course “Biotechnological measurements” is to teach the students the most important knowledge of the information and metrological assurance of the biotechnological processes with different methods and equipments for direct and indirect measurement of the variables and methods of data processing.

PREREQUISITES: Bioelectricalengineering Fundamentals, Electrical engineering, Electrical measumerents.

TEACHING METHODS: Classical lectures with visual aids. Laboratory works using laboratory manuals. Each student prepares a protocol for his laboratory work. Protocols are checked and estimated by the lecturer. Multimedia projector for lectures. Special laboratory equipment for laboratory works. Computers for process modelling.

METHOD OF ASSESSMENT: Written examination. Laboratory works assessment is also taken into account

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY: 1. Neykov A. A., Biotechnological Measurement and Control, Sofia, TU – Sofia, (textbook), 1990; 2. Neykov A. A., Radonov K., Djambasis K., Walewski, Methods, Algorithms and Equipments for Measurement and Control in Biotechnology, Sofia, Technika, 1992; 3. Neykov A. A., Djambasis K., Krastev K., Laboratory Exercisers of Biotechnological Measurement and Control, Sofia, TU – Sofia (textbook) 1988; 4. Bailey J. E. D. F. Ollis, Biochemical Engineering Fundamentals, vol. 1., vol. 2., Mir, Moscow, 1989.

DESCRIPTION OF THE COURSE


Name of the course:

Artificial Intelligence

Code: BAICE43

Semester: 7

Type of teaching:

Lectures, Laboratory work,

Course work

Lessons per week:

L – 2 hours

LW – 1,5 hours

Number of credits: 5

LECTURER:

Assoc. Prof. Ph.D. Dimitar Dimitrov (FA), tel. 965 2636, email dpd@tu-sofia.bg,

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: Uderstanding the essential principles of intelligent behavior, corresponding computational algorithms, and ideas for building practical intelligent systems. Getting practical skills in knowledge representation and reasoning, in designing simple architectures of intelligent agents, building knowledge bases for diagnostic, decision support and control systems.

DESCRIPTION OF THE COURSE: This is an introductory course. The field of Artificial Intelligence (AI) is presented as unified field from the perspective of rational behavior. Both approaches to AI - the symbolic (logical) and the behavioral (numerical) are presented as complementary (not contradictory). The main covered topics include: Intelligent agents, environments and behaviors. Principle of rationality, rational reasoning and rational acting. Formal logic methods for knowledge representation and reasoning in intelligent systems. Problem solving by searching – informed and heuristic search methods. Acting logically – planning methods and acting. Learning. Uncertain knowledge and reasoning. Robotics and AI – intelligent connection of perception to action. Outputs: other special disciplines and diploma project.

PREREQUISITES: Mathematics, Programming and Computer Application, Logic Modelling and Programming.

TEACHING METHODS: Lectures using slides, computer program handouts, laboratory protocols preparation and defence, work in teams, discussions. The laboratory and course work is provided with the supporting programming language PROLOG. The basic didactic approach is “understanding trough implementation”.

METHOD OF ASSESSMENT: One three-hours final exam (65%), plus laboratories (10%) plus course work (20%), plus class attendance, accuracy, etc. (5%).

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY: 1.Димитров, Д.Н. Никовски. Изкуствен интелект – второ преработено издание. ISBN 954-438-252-6. Изд.ТУ - София, 1999. 2. S. Russel. P. Norvig. Artificial Intelelgence. Prentice Hall, 2003. 3. Е. Чарнияк, Д. МакДермот. Въведение в изкуствения интелект. София, 1997. 4. Shapiro Enciclopedia of Artificial Intelligence. Wiley, New York, Two volumes, 1992. 5. N. Rowe. Artificial Intelligence throw Prolog. Prentice-Hall Int. Inc., 1990. 6. M. R. Genesereth, N. J. Nilsson. Logical Foundations of Artificial Intelligence. Morgan Kaufman Publ. Inc., 1987.


List OS5 (BAICE44– EСТК 5)

L5O1 Data and Signal Processing

L5O2 Electronic Measurements Transducers

L5O3 Automated Monitoring and Diagnostics

L5O4 Low-cost Automation Systems

L5O5 Data Analysis of Biotechnology Processes

L5O6 Control of Robots and Robotic Systems


DESCRIPTION OF THE COURSE


Name of the course:

Data and Signal Processing

Code: BAICE44

Semester: 7

Type of teaching:

Lectures

Laboratory exercises

Lessons per week:

L –2 hours

LW – 1.5 hours

Number of credits: 5

LECTURER:

Ass. Prof. G. Ruzhekov PhD, tel.: 965 24 70, email: rouzhekov@hotmail.com

Technical University of Sofia


COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.


AIMS AND OBJECTIVES OF THE COURSE: The main aim of the course is to get students familiar with the methods of digital signal and data processing, as well as the special features and applications of the signal processors.


DESCRIPTION OF THE COURSE: Described are the analogue to digital and digital to analogue converters and their characteristics, the signal processors and the system based on them and their advantages compared to ordinary systems. Attention of the course is mostly directed to processing of digital signals in time and frequency domain and its applications. Discussed are the connections between the characteristics of signals on the time and frequency domain and some typical applications of the methods of signal processing.

PREREQUISITES: Control Theory, Electrical Engineering Theory, Pulse and Digital Circuit Technique, Programming and Computer Application, Physics, Mathematics.

TEACHING METHODS: Lectures, using slides, laboratory and course work, work in teams, reports and course work description preparation and defence.

METHOD OF ASSESSMENT: Written final examination, including solving problems (60%); laboratory reports defence (40%).


INSTRUCTION LANGUAGE: Bulgarian language.


BIBLIOGRAPHY: 1. Ruzhekov G., Signal and Data processing, TU-Sofia, 2004. Ivanov R., Digital processing of the one-dimensional signals, Gabrovo, 2002., 3. Ifeachor E, B. Jerrvils, Digital Signal Processing – A practical Approach, Addison-Wesley Publishing Company 1993. 4. Ruzhekov G., Laboratory experiments of the digital signal processing with the digital signal processing, TU-Sofia, 1998.

DESCRIPTION OF THE COURSE


Name of the course:

Electronic Measurements Transducers

Code: BAICE44

Semester: 7

Type of teaching:

Lectures and

Laboratory work

Lessons per week:

L – 2 hours

LW – 1,5 hours

Number of credits: 5

LECTURER:

Assoc. Prof. Ph.D. P. Tzvetkov (FA) – tel.965 2382, email: tzvetkov@tu-sofia.bg

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: To provide fundamental theoretical and practical knowledge of modern electronics measurement instruments.

DESCRIPTION OF THE COURSE: The main topics concern electronic measurement systems and transducers. An essential part is devoted to the modulation transducers, non-linearity measurement transducers, programmable measurement amplifiers and reference time period, reference current and voltage sources.

PREREQUISITES: Mathematics, Electrical Engineering Theory.

TEACHING METHODS: Lectures, using slides, case studies, computer demonstrations, laboratory work from laboratory manual, work in teams, protocols preparation and defence.

METHOD OF ASSESSMENT: A two-hour exam (total mark 80%: 40% problems + 40% theory) plus laboratories (total 20%)

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY:

1. Йорданова С., П. Цветков. Приложно моделиране и симулиране. София, Heron Press Math Series, 2001, 92, ISBN 954-580-105-0. 2. Самоковлийски, А. Нейков, И. Коджабашев, Измервателни преобразуватели- лабораторни упражнения, София, Издателство на ТУ-София, 1980, 82. 3. Самоковлийски Д. Електрически измервателни преобразуватели. София, Издателство на ТУ-София, 1984, 95. 4. Станчев, И., Електронни аналогови измервателни преобразуватели (проблеми от теорията и метрологичното осигуряване в етапа на проектиране), София, Издателство на ТУ, 1992, 256.

DESCRIPTION OF THE COURSE

Name of the course:

Automated Monitoring and Diagnostics


Code: BAICE44

Semester: 7

Type of teaching:

Lectures,

Laboratory work

Lessons per week:

L – 2 hours

LW – 1,5 hours


Number of credits: 5


LECTURER:

Assoc. Prof. Ph.D. Eng. Zheko Bildirev (FA), tel: 965-29-60: e-mail: jsb@tu-sofia.bg

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: Special attention is paid to the fast operational identification of dynamic parameters in the automated systems. Special chapter on solution of optimal tasks by means of these identificational methods is included.

DESCRIPTION OF THE COURSE: Looks into the general problems, ideas and definitions of the technical diagnostics of automated systems, their capacity for work and the methods for its evaluation and forecasting.

PREREQUISITES: Knowledge in the field of measurement of non-electrical quantities and the theory of automatic control are needed.

TEACHING METHODS: Lectures, aided by diaprojector’s slides; labs on physical and computer models. Written materials and software products are given to the students.

METHOD OF ASSESSMENT: Written examination.

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY: 1. Билдирев Ж., Автоматичен контрол и диагностика, учебник за ТУ-София (до излизането на учебника по курса ще се ползват т.н. свитъци – “фототипни копия” на записките по лекциите.; 2. Билдирев Ж., Контрол и оптимизация в системите за автоматизация, хабилитационен труд, 1993.; 3. Пархоменко П. и др. Основы технической диагностики, кн.1, М., Энергия, 1976.; 4. Пархоменко П. и др. Основы технической диагностики, кн.2, М., Энергия, 1976.; 5. Иофинов С. и др. Контроль работоспособности трактора, Л., Машиностроение, 1985.; 6. Гаскаров Д., и др. Прогнозирование технического состояния радиоэлектронной аппаратуры, М., Радио, 1974.; 7. Киншт Н., и др. Диагностика электрический цепей, М., Энергоатомиздат, 1983.; 8. Силин В., и др. Автоматическое прогнозирование состояния аппаратуры управления и наблюдения, М., Энергия, 1973.

DESCRIPTION OF THE COURSE


Name of the course:

Low-cost Automation Systems

Code: BAICE44

Semester: 7

Type of teaching:

Lectures,

Laboratory work

Lessons per week:

L – 2 hours;

LW – 1.5 hours

Number of credits: 5

LECTURER:

Prof. D.Sc. Kostadin Naplatarov (FA) – tel.965 29 42 , еmail: naplatarov@tu-sofia.bg

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE:

To study the wide spread industrial systems, aggregates, installations and technology applications to distributed systems, dynamical systems from engineering (electrical, thermal, hydraulic, mechanical, control) etc. Basic structures, optimization and effectiveness of production are concern. At the end of the course the students are expected to be able to apply the methodology for investigation of continuous, discrete time and discrete-event processes and systems in the field of industry based on low-cost components, and to have basic knowledge and skills in using software, making decision on structure, components for building reliable automation systems models in real live industrial systems.

DESCRIPTION OF THE COURSE:

The main topics concern: industrial technology for thermal heating exchange, mass exchange, electrical, hydraulic, mechanical, process control systems, basic structure, effectiveness measurable criteria for optimization. With solid laboratory support the technology (natural physics-chemical) aspect of problems is clearly demonstrate. The knowledge received in this course via systematic training with real technology is giving the students rational thinking about problems in industry.

PREREQUISITES: Control Theory, System Identification, Process Control, Control Instrumentation , Physics, Technical Mechanics, Electrical Measurements.

TEACHING METHODS: Lectures, using slides, case studies, laboratory work from laboratory manual, work in teams, protocols preparation and defence.

METHOD OF ASSESSMENT: Two hours assessments at end of semester

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY: 1.Наплатаров К. Х. Промишлени системи за нискостойностна автоматизация. /Под печат/. 2.Хаджийски М. Б. Автоматизация на технологични процеси в химичната и металургичната промишленост., С., Техника 1988. 3.Мумджиян Г. С. Автоматично управление и регулиране на топлинни процеси., С., Техника, 1987. 4.Фархи О. А., А. М. Тодоров, Е. К .Николов. Промишлени системи за автоматизация., ВМЕИ, Варна, 1989. 5.Хаджийски М. Б., К. Д. Велев, Г. Р. Сотиров, И. Г. Калайков. Методи и алгоритми за управление. С. Техника, 1992.

DESCRIPTION OF THE COURSE


Name of the course:

Data Analysis of Biotechnology processes

Code: BAICE44

Semester: 7

Type of teaching:

Lectures,

Laboratory work

Lessons per week:

L – 2 hours;

LW – 1.5 hours

Number of credits: 5

LECTURER:

Assistant Prof. Tzanko Georgiev (FA) – tel.: 965 2408, email: tzg@tu-sofia.bg

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: To teach the students the most important methods of the data analysis of the biotechnological processes: experimental design, regression analysis and analysis of variance.

DESCRIPTION OF THE COURSE: The biotechnology is multi - branch science. This is a reason to introduce the knowledge of the students in the area of the data analysis of the biotechnological processes. The main topics concern primary data processing, experimental design, linear and non-linear regression methods, stepwise regression, ridge regression and analysis of variance

PREREQUISITES: Bioelectricalengineering Fundamentals, Fermentation Technologies, Biotechnological Measurements, System Identification.

TEACHING METHODS: Classical lectures with visual aids. Laboratory works using laboratory manuals. Each student prepares a protocol for his laboratory work. Protocols are checked and estimated by the lecturer. Multimedia projector for lectures. Special laboratory equipment for laboratory works. Computers for process modelling

METHOD OF ASSESSMENT: Written examination. Laboratory works assessment is also taken into account

INSTRUCTION LANGUAGE: Bulgarian

BIBLIOGRAPHY: 1. Birukov W. W., W. M. Kantare, Optimisation of the Batch Processes for Microbial Synthesis, Moscow, Nauka, 1985 2. Bojanov E, I. Wuchkov, Statistical inferences in Enterprises and Scientific Investigations, Technika, Sofia, 1970; 3. Wuchkov I, Experimental Investigations and Identification, Sofia, Technika, 1990; 4. Daniel K., Application of the Statistics in Industrial Ezperiments, Mir, Moscow,1979; 5. Draper N. R., Smith H., Applied Regression Analysis, Moscow, vol. 1, vol. 2, Finansi I Statistika, 1986; 6. Staniskis J., Optimal Control of Biotechnological Processes, Vilnius, Mokslas, 1984; 7. Hartman K., E Letckii, W. Shefer, Experimental Design in Investigation of Technological Processes, Moscow, Mir, 1977.

DESCRIPTION OF THE COURSE


Name of the course:

Control of Robots and Robotic Systems

Code: BAICE44

Semester: 7

Type of teaching:

Lectures,

Laboratory work

Lessons per week:

L – 2 hours;

LW – 1.5 hour

Number of credits: 5

LECTURER:

Assoc. Prof. Ph.D. Vassil Balavessov (FA) – tel.: 965 3258, email balaves@tu-sofia.bg

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: At the end of the course the students should know the specific features of robots as control objects and they are expected to be able to solve engineering problems in planning and control of motions, as well as to analyze and investigate robot performance through modelling and simulation.

DESCRIPTION OF THE COURSE: Modern methods for control of robots and robotic systems are studied. Special attention is paid to the problems of the planning and the control of smooth joint and world trajectories. Main accent is put on control and stabili­zation of a priori planned robotic motions, including robust stabilization design and computational aspects. The main topics concern: Planning of robotic motions: in joint and Cartesian coordinates; Design of robots trajectories by Bezier curves; Kinematic control of robots; Pseudoinvrersion and its applications; Dynamic modelling of manipu­la­tion systems; Non-linear control methods: stability and practical issues; Robot force control; Impedance control; Robot motion modelling and simulation.

PREREQUISITES: Control Theory, Electrical Engineering Theory, Mechanics, Robotic Manipulators, Information and Sensor Systems in Robotics.

TEACHING METHODS: Lectures using transparencies and multimedia, laboratory exer­cises using computer simulations, operational robot and robotized machining center.

METHOD OF ASSESSMENT: Open book written examination during the session.

INSTRUCTION LANGUAGE: Bulgarian.

BIBLIOGRAPHY: 1 Fu K.S., Gonzalez R. C., Lee C. S. G. Robotics: Control, Sensing, Vision and Intelligence, McGraw–Hill,. NY, 1989 (a Russian translation is available). 2 Shahinpoor, M. A Robot Engineering Textbook, Harper&Row, NY,1990 (a Russian translation is available). 3 Zamanov W., Karastoianov D., Sotirov. Z., Mechanics and control of robots, Sofia, 1993 (in Bulgarian). 4 Asada H. and Slotine J.-J.E. Robot Analysis and Control, A Wiley-Interscience Publication, New York, 1986. 5 Craig J. J. Introduction to Robotics: Mecha­nics & Control, Addison Wesley , Reading, Mass, 1986. 6 The ZODIAC, Theory of Robot Control, C. C. de Wit, B. Siciliano, and G. Basten (Eds), Springer-Verlag, 1996. 7. Paul R.P. Robot Manipulators: Mathematics, Programming and Control, MIT Press, Cambridge, Mass., 1981.


List OS6 (BAICE45–EСТК 5)

L6O1 Engineering Methods for Nonlinear Syst. Analysis

L6O2 Electromagn. Compatib.of Measurem. and Control

L6O3 Control Systems of Electric Drives

L6O4 Switching Logic Control

L6O5 Control Systems for Biotechnological Enterprises

L6O6 Design of Robots and Robotic Systems


DESCRIPTION OF THE COURSE


Name of the course:

Engineering Methods for Nonlinear Systems Analysis

Code: BAICE45

Semester: 7

Type of teaching:

Lectures,

Laboratory work

Lessons per week:

L – 2.0 hours

LW – 1.5 hours

Number of credits: 5


LECTURER:

Assoc. Prof. Elena Haralanova, PhD, (FA) tel.: 965-2526, email: elhar@tu-sofia.bg

Ass. Prof. Kamen Perev, PhD , (FA) tel.: 965-3459, email: kperev@tu-sofia.bg

Technical University of Sofia

COURSE STATUS IN THE CURRICULUM: Optional for the students specialty Automation, Information and Control Engineering, BEng programme, Faculty of Automation.

AIMS AND OBJECTIVES OF THE COURSE: The goal of this course is to present the basic models and methods for analysis and design of nonlinear systems.

DESCRIPTION OF THE COURSE: The course considers the main nonlinear system models for exploring the specific nonlinear phenomena like limit cycles, more than one equilibrium points, dependence on initial conditions and the input signals type, different types of stability and many others. Both, the analytic methods for system analysis, as well as more applied approaches using different types of linerization are presented. For the purpose of nonlinear system simulation, the course offers an introduction to the numerical procedures for solving nonlinear differential equations. The main methods for nonlinear systems design are also discussed.

PREREQUISITES: Mathematics I-III, Electrical Engineering Theory, Control Theory, Engineering Methods for Linear Systems Analysis.

TEACHING METHODS: Class lectures and laboratory experiments. The laboratory experiments are performed by using the software package of MATLAB/SIMULINK.

METHOD OF ASSESSMENT: Written final examination, including solving problems (80%); laboratory reports defence (20%).

INSTRUCTION LANGUAGE: Bulgarian language.

BIBLIOGRAPHY: 1. Ishtev, K., Automatic control theory, King Publ., 2000. 2. Slotine, J., W. Li, Applied nonlinear control, Prentice Hall, 1991. 3. Geldner, K., S. Kubik, Nonlinear control, systems, Mir, 1987.

DESCRIPTION OF THE COURSE


Name of the course:

Electromagnetic Compatibility in Measurements and Control

Code: BAICE45

Semester: 7

Type of teaching:

Lectures and Tutorials

Lessons per week:

L – 2 hours;

T – 1.5 hours

Number of credits: 5
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