Modern Theories, Methods and Tools for Creating Automation System
Description: Methods of analysis and synthesis of control systems under conditions of incomplete certainty. Methods for describing control objects in state space coordinates. The concepts of observability, controllability and identifiability in the state space. Methods of the theory of absolute stability. Methods of the theory of optimal control. Fundamentals of building adaptive ACS.
Amount of credits: 5
Course Workload:
| Types of classes | hours |
|---|---|
| Lectures | 15 |
| Practical works | 30 |
| Laboratory works | |
| SAWTG (Student Autonomous Work under Teacher Guidance) | 30 |
| SAW (Student autonomous work) | 75 |
| Form of final control | Exam |
| Final assessment method | writing exam |
Component: Component by selection
Cycle: Profiling disciplines
Goal
- Formation of knowledge on modern trends in the development of means and systems of automation and control, principles of construction and use of these systems in various fields of human activity, methods and tools for developing mathematical, linguistic, informational and software management systems, preparation for independent solution of theoretical and applied problems in the field of automation.
Objective
- to acquaint students with the trends in the development of science and technology in the field of studying dynamic properties and synthesis of robust and invariant systems;
Learning outcome: knowledge and understanding
- Students should know and understand the basic theories, methods and tools for creating automation and control systems.
Learning outcome: applying knowledge and understanding
- -Ability to apply modern trends in the theory of automation and control in solving practical problems; -Ability to use methods of analysis and synthesis of control systems in conditions of incomplete certainty, methods of describing objects, building robust and adaptive control systems.
Learning outcome: formation of judgments
- The ability to independently apply the methods and means of cognition, learning and self-control, to be aware of the prospects of intellectual, cultural, moral, physical and professional self-development and self-improvement, to be able to critically assess their own strengths and weaknesses.
Learning outcome: communicative abilities
- The ability to work effectively individually and as a member of a team, demonstrating the skills of managing separate groups of performers, including on interdisciplinary projects, be able to show personal responsibility, adherence to professional ethics and standards of professional conduct.
Learning outcome: learning skills or learning abilities
- Students should have the skills to perform calculations to analyze the stability, accuracy and quality of automation and control systems
Teaching methods
Technology of educational and research activities
Communication technologies (discussions, press conference, brainstorming, educational debates, etc.)
Information and communication (including remote) 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 | Practical work 1 | 0-100 |
| Practical work 2 | ||
| Practical work 3 | ||
| Boundary control 1 | ||
| 2 rating | Practical work 4 | 0-100 |
| Practical work 5 | ||
| Boundary control 2 | ||
| 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 |
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
- Introduction
- Methods of analysis and synthesis of control systems
- Observability, identifiability, stability
- Robust and invariant systems
- Control optimization criteria
- Extreme regulation systems
Key reading
- Metody klassicheskoi i sovremennoi teorii avtomaticheskogo upravleniıa. Uchebnik v pıati tomah/Pod red. K.A. Pupkova, N.D. Egupova. – M.: MGTU im. Baumana. - 2004. 2.
- Metody robastnogo, neiro-nechetkogo i adaptivnogo upravleniıa. Uchebnik dlıa vuzov/ Pod red. N.D. Egupova. – M.: MGTU im. Baumana. – 2002.
- Leonenkov A.V. Nechetkoe modelirovanie v srede MatLAV i TESN. – SPb.: BHV-Peterburg, 2003.
