Automation of Engineering Systems
Description: Modern control systems for technical objects are considered. The principles of building automation systems, methods for obtaining mathematical models, calculating industrial regulators, as well as managing objects with a significant level of disturbances are studied. Information about the features of digital control of technical objects is presented.
Amount of credits: 5
Пререквизиты:
- Local systems automation and control
Course Workload:
| Types of classes | hours |
|---|---|
| Lectures | 15 |
| Practical works | |
| Laboratory works | 30 |
| SAWTG (Student Autonomous Work under Teacher Guidance) | 30 |
| SAW (Student autonomous work) | 75 |
| Form of final control | Exam |
| Final assessment method | oral exam |
Component: University component
Cycle: Profiling disciplines
Goal
- Theoretical and practical development of methods and tools for building control systems for technical objects
Objective
- Acquiring knowledge and skills of construction, mathematical description, basic ideas, calculation methods and application of control systems for technical objects
Learning outcome: knowledge and understanding
- know and understand the basic principles and methods of automation of production and technical systems. This includes understanding the principles of building automated systems, using sensors and actuators, and using software to control and monitor technical processes.
Learning outcome: applying knowledge and understanding
- apply the acquired knowledge and understanding for the design, development and implementation of automated control systems in various fields of industry and technology, analyze technical processes, select suitable automation technologies
Learning outcome: formation of judgments
- form judgments about the applicability and effectiveness of automation methods in various technical systems, evaluate the advantages and disadvantages of various approaches to automation, and also make informed decisions when choosing technologies and automation methods for specific tasks and conditions.
Learning outcome: communicative abilities
- Explain complex technical concepts, present results of your work, and discuss automation issues with other project or team members.
Learning outcome: learning skills or learning abilities
- systematize information, analyze technical concepts and automation methods, and search for and use relevant sources of information to solve problems in this area.
Teaching methods
Technologies of educational and research activities
Modular learning technology
Information and Communication Technologies
Assessment of the student's knowledge
Teacher oversees various tasks related to ongoing assessment and determines students' current performance twice during each academic period. Ratings 1 and 2 are formulated based on the outcomes of this ongoing assessment. The student's learning achievements are assessed using a 100-point scale, and the final grades P1 and P2 are calculated as the average of their ongoing performance evaluations. The teacher evaluates the student's work throughout the academic period in alignment with the assignment submission schedule for the discipline. The assessment system may incorporate a mix of written and oral, group and individual formats.
| Period | Type of task | Total |
|---|---|---|
| 1 rating | Performing and defending laboratory work 1 | 0-100 |
| Performing and defending laboratory work 2 | ||
| Performing and defending laboratory work 3 | ||
| Performing and defending laboratory work 4 | ||
| Performing and defending laboratory work 5 | ||
| Performing and defending laboratory work 6 | ||
| 2 rating | Performing and defending laboratory work 7 | 0-100 |
| Performing and defending laboratory work 8 | ||
| Performing and defending laboratory work 9 | ||
| Performing and defending laboratory work 10 | ||
| Performing and defending laboratory work 11 | ||
| Performing and defending laboratory work 12 | ||
| Total control | Exam | 0-100 |
The evaluating policy of learning outcomes by work type
| Type of task | 90-100 | 70-89 | 50-69 | 0-49 |
|---|---|---|---|---|
| Excellent | Good | Satisfactory | Unsatisfactory | |
| Performing and defending laboratory work | A complete, detailed answer to the question posed is given, the totality of conscious knowledge about the object is shown, the main provisions of the topic are conclusively revealed; the answer shows a clear structure, a logical sequence that reflects the essence of the concepts, theories, and phenomena being revealed. Knowledge about an object is demonstrated against the background of understanding it in the system of a given science and interdisciplinary connections. The answer is stated in literary language in scientific terms. There may be shortcomings in the definition of concepts, which are corrected by the student independently during the answering process. | A detailed answer to the question posed is given, the ability to identify essential and non-essential features and cause-and-effect relationships is demonstrated. The answer is clearly structured, logical, and stated in scientific terms. However, minor errors or omissions were made, which were corrected by the student with the help of “leading questions.” | The answer given is insufficiently complete and insufficiently detailed. The logic and consistency of presentation have violations. Errors were made in the disclosure of concepts and the use of terms. The student is not able to independently identify essential and non-essential features and cause-and-effect relationships. The student can concretize generalized knowledge by proving its main points with examples only with the help of the teacher. Speech design requires amendments and corrections. | A complete, detailed answer to the question posed is given, the totality of conscious knowledge about the object is shown, the main provisions of the topic are conclusively revealed; the answer shows a clear structure, a logical sequence that reflects the essence of the concepts, theories, and phenomena being revealed. Knowledge about an object is demonstrated against the background of understanding it in the system of a given science and interdisciplinary connections. The answer is stated in literary language in scientific terms. There may be shortcomings in the definition of concepts, which are corrected by the student independently during the answering process. |
Evaluation form
The student's final grade in the course is calculated on a 100 point grading scale, it includes:
- 40% of the examination result;
- 60% of current control result.
The final grade is calculated by the formula:
| FG = 0,6 | MT1+MT2 | +0,4E |
| 2 |
Where Midterm 1, Midterm 2are digital equivalents of the grades of Midterm 1 and 2;
E is a digital equivalent of the exam grade.
Final alphabetical grade and its equivalent in points:
The letter grading system for students' academic achievements, corresponding to the numerical equivalent on a four-point scale:
| Alphabetical grade | Numerical value | Points (%) | Traditional grade |
|---|---|---|---|
| A | 4.0 | 95-100 | Excellent |
| A- | 3.67 | 90-94 | |
| B+ | 3.33 | 85-89 | Good |
| B | 3.0 | 80-84 | |
| B- | 2.67 | 75-79 | |
| C+ | 2.33 | 70-74 | |
| C | 2.0 | 65-69 | Satisfactory |
| C- | 1.67 | 60-64 | |
| D+ | 1.33 | 55-59 | |
| D | 1.0 | 50-54 | |
| FX | 0.5 | 25-49 | Unsatisfactory |
| F | 0 | 0-24 |
Topics of lectures
- Basic ideas and principles of building automation systems in engineering
- The problem of management, accepted terms and principles of management
- Sensors of process variables in automation systems
- Industrial networks and interfaces
- Typical automatic control systems
- Signal processing in process control systems
- Types of mathematical models
- Drawing up the structure of relationships between the variables of the mathematical model
- Experimental and statistical methods for obtaining mathematical models
- Application of the theory of probability in obtaining mathematical models
- Managing multichannel objects
- Requirements for optimality criteria
- Some methods used in dynamic optimization
- L's maximum principle
- Nonlinear programming
Key reading
- Metody klassicheskoi i sovremennoi teorii avtomaticheskogo upravleniya: Uchebnik v 5-i tomah / Pod red. K.A. Pupkova, N.D. Egupova. – M.: İzdatelstvo MGTU im. N.E. Baumana. 2004. – 656 s.
- Spravochnik po teorii avtomaticheskogo upravleniya /Pod red. A.A. Krasovskogo. – M.: Nauka, 2007. – 712 s.
- Avtomaticheskoe upravlenie v himicheskoi promyşlennosti: Uchebnik dlya vuzov. Pod red. E.G. Dudnikova. – M.: Himiya, 1987. 368 s.
- Pyavchenko T.A., Finaev V.İ. Avtomatizirovannye informatsionno-upravlyayuşie sistemy. – Taganrog: TRTU, 2007. – 270 s.
- Glinkov G.M., Makovskii V.A. ASU TP v chernoi metallurgii. – M.: Metallurgiya, 1999. – 310 s.
Further reading
- Voronov A.A. Osnovy teorii avtomaticheskogo regulirovaniya i upravleniya. Uchebnoe posobie dlya vuzov. M. : Vysşaya şkola, 2010, 519 s.
- Miroşnik B.R. Teoriya avtomaticheskogo upravleniya. Lineinye sistemy. – SPb.: Piter, 2005. – 336 s.
