Microprocessor-Based Controller Hardware and Software Tools

Appendix 1

 Course: Microprocessor-Based Controller Hardware and Software Tools

Programme Summary

Major: 27.04.04 Automated Control

Degree: Master

Course units:

Section 1. Microprocessor-based hardware for designing control systems

• Unit 1. S7-200/300/400/1200
• Unit 2. Omron, ‘Oven’, Delta

Section 2. Development tools for microprocessor programming.

• Unit 3. S7-200/300/400/1200.
• Unit 4. Omron, ‘Oven’, Delta

Section 3. Programming of microprocessor-based hardware with the help of low-level (LAD, STL) and high-level languages

• Unit 5. Introduction to the LAD and STL programming
• Unit 6. Ladder diagram programming
• Unit 7. Sequence control programming

Section 4. Microprocessor-based hardware. AS, Ethernet and Profibus networks.

• Unit 8. The modular structure of controllers
• Unit 9. Configuring controller network communication

Section 5. Programming of data exchange in a microprocessor controller network

• Unit 10. Programming for S7-300/400
• Unit 11. Programming for ‘Oven’, Omron, Delta

Section 6. Design of microprocessor-based control systems

• Unit 12. Control software structuring
• Unit 13. Setting up dispatcher control interfaces when doing the controller programming

Section 7. Integrated development of control systems from microprocessor controllers to SCADA systems

• Unit 14. Preparing the controller software for communication with the dispatch control system
• Unit 15. Configuring the dispatch control visualization system

Section 8. Communication interfaces with microprocessor-based hardware. Programming of data exchange between SCADA and microprocessor-based hardware.

• Unit 16. Communication with the S7-300/300 controllers
• Unit 17. DDE and OPC

Section 9. Use of microprocessor-based hardware and SCADA systems for process data acquisition, storage and processing.

• Unit 18. Interaction between SCADA and databases
• Unit 19. Setting up alarms and reporting

Section 10. Distributed process visualization systems.

• Unit 20. Development of the client/server architecture
• Unit 21. SCADA back-up system

Section 11. Organizing personnel during check-ups and troubleshooting

• Unit 22. Automatic diagnostics of I/O errors
• Unit 23. Error masking, input signal forcing and overriding

Section 12. Checking up and troubleshooting of modular microprocessor-based control systems

• Unit 24. Processing of microprocessor asynchronous errors
• Unit 25. Processing of asynchronous errors associated with program failures

Course contents:

This course teaches about the design, operation and programming of microprocessor-based hardware of different levels and applications. The course is aimed at teaching the student how to structure control tasks and develop controller algorithms, how to identify the most efficient programming language and do the programming of microprocessor-based and SCADA systems.

Activities:

• Teacher-led group activities in a classroom;
• Extracurricular self-study of the teacher’s assignments and tasks, including the use of educational facilities (obligatory);
• Office-hours.

Total hours – 504

Total points – 14

Laboratory activities – 144

Midterm assessment – Examination

History and Methodology of Control Science and Engineering

Appendix 1

Course: History and Methodology of Control Science and Engineering

Programme Summary

Major: 27.04.04 Automated Control

Degree: Master

Course units:

Section 1. Evolution of the classical control theory.

• Unit 1. Cybernetics. The history of automation
• Unit 2. The current standing of control science
• Unit 3. Evolution of computational means
• Unit 4. Evolution of artificial intelligence systems.
• Unit 5. Evolution of robotic systems

Section 2. Methodology of control science.

• Unit 6. Stages of building the scientific knowledge. Scientific methods and their classification.
• Unit 7. Process, system and situational approaches to management.
• Unit 8. Methods and algorithms of solving nontrivial engineering problems. Copyright

Course contents:

This course is aimed at giving the students a comprehensive understanding of the evolution of control science in its theoretical and practical aspects and at building skills of adequate assessment of milestone events in the history of the science. The students will learn to effectively work with the relevant historical records and understand the methodology of science and scientific knowledge.

The following aspects are covered in the course to achieve the above aim:

• The evolution of control science and the identification of key trends and inherent relationships that define the evolution;
• Methodology of science and scientific knowledge
• The approaches and theories that had a major effect on the control science and its practical methods.

Activities:

• Teacher-led group activities in a classroom;
• Extracurricular self-study of the teacher’s assignments and tasks, including the use of educational facilities (obligatory);
• Office-hours.

Total hours – 108

Total points – 3

Laboratory activities – 18

Midterm assessment – Pass/fail examination

Mathematical Modelling of Control Objects and Systems

Appendix 1

 Course: Mathematical Modelling of Control Objects and Systems

Programme Summary

Major: 27.04.04 Automated Control

Degree: Master

Course units:

Section 1. Classification of system model types. Main application criteria.

• Unit 1. Basic concepts of modelling. Mathematical modelling
• Unit 2. Model types and classification. Task setting in process and control system modelling.

Section 2. Modelling techniques for complex objects and systems

• Unit 3. Modelling of physical processes defined in terms of common differential equations.
• Unit 4. Numerical solution of differential equations. Building numerical models of control systems.
• Unit 5. The use of operational calculus in building models of control objects and systems.

Section 3. Control system models

• Unit 6. System transfer functions. Elementary and standard units of control systems. Transient and frequency responses. Combination of system units.
• Unit 7. Controller. Controller setup. Magnitude optimum methods. Transients and the quality of transients. Numerical setup methods and setup criteria.
• Unit 8. Input/output system models. Cascade controllers. Cascade controller setup methods.

Section 4. Modelling of complex control objects and systems

• Unit 9. Building and algorithmization of control system connectionist models.
• Unit 10. Connectionist regression model trainable with empirical data.
• Unit 11. The use of fuzzy logic in control system modelling.
• Unit 12. Algorithmization and software implementation of fuzzy logic based models

Course contents:

This course teaches about the main techniques of mathematical modelling and control object modelling giving an insight into mathematical modelling as a scientific method and a research tool. The aim of the course is to give the students an idea about how to select mathematical tools to describe different objects. The course also aims to build some practical skills of using computer modelling to simulate process control systems. 

Activities:

• Teacher-led group activities in a classroom;
• Extracurricular self-study of the teacher’s assignments and tasks, including the use of educational facilities (obligatory);
• Office-hours.

Total hours – 288

Total points – 8

Laboratory activities – 54

Midterm assessment – Examination

Current Problems of Control Theory

Appendix 1

 Course: Current Problems of Control Theory

Programme Summary

Major: 27.04.04 Automated Control

Degree: Master

Course units:

Section 1. Control theory and the evolution of the present-day society.

• Unit 1. Key characteristics and features of complex control objects and systems.
• Unit 2. The problem of synthesis as the core problem of the current control theory
• Unit 3. Optimization approach to management
• Unit 4. Synergy approach to management.

Section 2. The current problems of building control systems.

• Unit 6. Modelling of complex dynamic control systems.
• Unit 7. Decomposition and aggregation when studying complex dynamic control systems

Section 3. Key research areas in management.

• Unit 8. Artificial intelligence techniques in control theory
• Unit 9. Neuron networks and control systems
• Unit 10. Fuzzy control systems
• Unit 11. Distributed parameter systems.
• Unit 12. Evolution of automation and control devices.
• Unit 13. Methods and control in social and economic systems.

Course contents:

This course covers some major problems of the present-day control theory. The students will learn about the current developments of control systems of various applications, study the current control system patterns and find out how control systems are implemented with the help of advanced devices.

Activities:

• Teacher-led group activities in a classroom;
• Extracurricular self-study of the teacher’s assignments and tasks, including the use of educational facilities (obligatory);
• Office-hours.

Total hours – 216

Total points – 6

Laboratory activities – 36

Midterm assessment – Examination