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Intelligent Control Systems
Major: Automation and computer-integrated technologies
Code of subject: 7.174.00.O.001
Credits: 3.00
Department: Automation and Computer-Integrated Technologies
Lecturer: Roman Vitalii Ivanovych, assistant professor, candidate of technical sciences
Semester: 1 семестр
Mode of study: денна
Завдання: - General competences:
K1. The ability to conduct research at an appropriate level.
K2. The ability to generate new ideas (creativity).
K3. Abstract thinking, analysis and synthesis.
- special (professional, subject) competences:
K5. The ability to automate complex technological objects and complexes, to create cyberphysical systems based on intellectual management methods and digital technologies using databases, knowledge databases, artificial intelligence methods, robotic and intellectual mechatronic devices.
K7. The ability to use modeling and optimization methods to research and increase the efficiency of systems and processes of control of complex technological and organizational and technical objects.
Learning outcomes: PR01. Apply intellectual control methods to create effective automation systems based on the use of databases and databases, artificial intelligence methods, digital and network technologies, robotic and intellectual mechatrony devices.
PR03. Be able to apply modern modeling and optimization methods to research and create effective automation systems with complex technological and organizational and technical objects.
Required prior and related subjects: 1. Methods of modern control theory.
2. Modeling and optimization of control systems.
3. Integration technologies in automated control systems
Summary of the subject: The first lecture session is devoted to highlighting the role and place of the discipline in the hierarchy of the educational and scientific program. The student learns about the scope, structure, purpose and tasks of the discipline; the lecturer informs the criteria for knowledge assessment and reporting. The following lectures are dedicated to covering the following topics: basic concepts and definitions of artificial intelligence and expert systems (topic 1); basic concepts of intelligent management (topic 2); intelligent control systems based on fuzzy logic (topic 3); intelligent control systems based on artificial neural networks (topic 4); intelligent control systems based on genetic algorithms (topic 5); intelligent control systems based on cognitive maps (topic 6). The last (final) lecture session is devoted to advisory questions for preparing for the exam in the discipline "Intelligent control systems".
Опис: 1. Artificial intelligence and expert systems. Basic concepts and definitions. Artificial intelligence systems. Knowledge representation models. Knowledge engineering
2. Intelligent control. The idea of intelligent control. Hierarchical organization of intelligent control systems. Entropy as a measure of the quality of the intelligent control process. Optimization of control processes in intelligent control
3. Intelligent control systems based on fuzzy logic. Fuzzy plural and linguistic variable. Operations on fuzzy sets. Fuzzy algorithm and defuzzification. Fuzzy model of dynamic systems. Synthesis of fuzzy control algorithms. Fuzzy adaptive control system. Stability of systems with fuzzy regulators. Criticism and application examples of fuzzy logic
4. Intelligent control systems based on artificial neural networks. Formation of the theory of artificial neural networks. A formal neuron. Architecture of artificial neural networks. Structures of artificial neural networks. Tasks and learning methods. Backpropagation algorithm. Application of artificial neural networks for control tasks. Schemes of neural network control
5. Intelligent control systems based on genetic algorithms. Evolutionary methods. Genetic algorithms. Examples of implementation of genetic algorithms
6. Intelligent control systems based on cognitive maps. Cognitive modeling. Construction of cognitive maps. Examples of the use of cognitive maps for control systems
Assessment methods and criteria: The following methods of assessing the level of achievement of learning outcomes are used when teaching the discipline:
1) frontal and selective oral surveys of students at lectures and laboratory classes;
2) selective verification of the availability and fullness of the lecture notes at the end of the semester;
3) verification of correctness of execution and registration of reports to laboratory work;
4) oral protection of reports to laboratory work;
5) oral and written examination of the exam (answers to the examination of the examination ticket)
Критерії оцінювання результатів навчання: 1. Current control (30 points):
1.1. Complete completion of all laboratory work (6).
1.2. Completion of all reports for laboratory work according to methodical requirements (6).
1.3. Oral defense of all laboratory works (18).
2. Examination control (70 points):
2.1. Written component (50)
2.2. Oral component (20)
3. Together for discipline (100 points)
Порядок та критерії виставляння балів та оцінок: 1. CURRENT CONTROL
1.1. The student must be present at all laboratory classes (or their online version).
1.2. Each completed laboratory session is valued at 1 point.
1.3. Only after completing the laboratory work, the student can defend a report on it.
1.4. Before the defense, the student must prepare a report for the laboratory work. The report must contain the completed tasks of the laboratory work according to the individual version of the student, and according to the requirements for their design (contained at the end of each manual).
1.5. Each correctly prepared laboratory report is valued at 1 point.
1.6. The defense of the report is an oral answer to three control questions on laboratory work, which are included at the end of the manual.
1.7. Each correct answer during the defense of the report is valued at 1 point. At the same time, only one chance is given for the answer in a short period of time (up to 1 minute). If the student did not answer the question, he does not receive a point, and moves on to the next question.
1.8. After defending the report, the student can receive a grade in the range of 0... 2 points.
2. EXAMINATION CONTROL
2.1. Examination control consists of two components - written and oral.
2.2. During the written component of the examination control, the student receives a ticket containing theoretical and practical tasks from the entire course of the discipline.
2.3. During the oral component of the examination control, the student receives a certain number (depending on the difficulty) of oral questions from the teacher on the topics of the entire discipline course. The correct answer to each of the questions is evaluated in the range of 5...10 points. If the answer to the question is incorrect, the student receives 0 points.
3. ASSESSMENT FOR THE DISCIPLINE
The minimum acceptable total grade for the discipline out of 100 is 51 points. In the case of a lower value than 51, the student goes to re-study the discipline.
Recommended books: 1. Plant Intelligent Automation and Digital Transformation. Process and Factory Automation / Swapan Basu. – Academic Press, 2023. – 546 pages.
2. Advanced Control Engineering / Roland S. Burns. – Butterworth-Heinemann, 2011. – 450 pages.
3. Artificial intelligence in energy: analytical report / O.M. Sukhodolya. - Kyiv : NISS, 2022. - 49 pages. (in Ukrainian)
4. Robotics and Automation in the Food Industry. Current and Future Technologies / Darwin G. Caldwell (editor). – Woodhead Publishing, 2013. – 503 pages.
5. Intellectual data analysis (Date Mining) / V.F. Sytnik, M.T. Krasnyuk. - Kyiv : Kyiv National Economic University, 2007. - 376 pages. (in Ukrainian)
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