EEI354 Adaptive Systems in Industrial Electronics

Code EEI354
Name Adaptive Systems in Industrial Electronics
Status Compulsory/Courses of Limited Choice
Level and type Post-graduate Studies, Academic
Field of study Power and Electrical Engineering
Faculty
Academic staff Mihails Gorobecs, Andrejs Potapovs
Credit points 3.0 (4.5 ECTS)
Parts 1
Annotation Study course is devoted to adaptive systems that automatically adjust themselves to outside conditions and changes of electric or electro-mechanic control object, changing structure and parameters of control device providing necessary quality of control. Within the study course main features of the adaptive system are the possibilities of embedded systems for self-organization, self-learning and self-regulation with the use of fuzzy logic, associative memory, neural networks and other methods, solving the tasks of extreme control and optimization, automation control as well as searching, recognition, classification, clasterization tasks are studied..
Contents
Content Full- and part-time intramural studies Part time extramural studies
Contact hours Independent work Contact hours Independent work
Control systems of the complex electric and mechanic objects. Closed systems. 2 3 1 4
Controllable objects and methods of expert evaluation. Criteria of control quality. 2 3 1 4
Adaptive identification in control systems. Algorithm of adaptive identification. Searching algorithms and adaptation. 2 3 1 4
Uninterruptable inertia objects. Adaptation of frequency in the inertia objects. 2 3 1 4
Extreme control. Self-regulated extreme control systems. 2 3 1 4
Adaptation in gradient methods. Self-learning in stochastic processes. 2 3 1 4
Adaptive and intelligent automatic control systems. 2 3 1 4
Self-regulated adaptive automatic control systems. 2 3 1 4
Adaptive control systems with optimization of dynamic and static modes. 2 3 1 4
Self-organized and self-learning adaptive automated control systems. 2 3 1 4
Adaptive automated control systems on the basis of fuzzy logic. 2 3 1 4
Adaptive automated control systems on the basis of expert systems. 2 3 1 4
Adaptive automated control systems on the basis of associative memory. 2 3 1 4
Adaptive automated control systems on the basis of neuron networks. 2 3 1 4
Self-organization principles and adaptation processes. Classification of adaptive sets. 2 3 1 4
Adaptive analysis of main components. Adaptation of models. 2 3 1 4
1. practical class: programming of adaptive methods for PLC in automated control systems. 4 6 2 8
2. practical class: programming of adaptive algorithms for microcontrollers in automated control systems. 4 6 2 8
3. practical class: adaptive control system of transport system electric drive on the basis of neural networks. 4 6 2 8
4. practical class: adaptive control system of traffic lights and electric transport flow. 4 6 2 8
Total: 48 72 24 96
Goals and objectives
of the course in terms
of competences and skills 		The goal of the course is to provide knowledge about basic principles and development approaches of adaptive systems in industrial electronics. The tasks of the study course are to give knowledge about adaptive automatic control systems, their features and to teach students to apply adaptive methods for the complex objects control.
Learning outcomes
and assessment 		Is able to use languages for controllers programming in the realization of adaptive control methods for the control of electric and electro-mechanic objects. - Practical class. Study project.
Is able to develop robots and other electric devices adaptive control programs. - Practical class. Study project.
Is able to define principles of adaptive systems, features and parameters, describe methods of adaptive control, and control tasks. - Theoretical examinational questions.
Is able to develop adaptive computer models for the systems robots and other electric devices automatization and control in Simulink environment. - Practice in computer class. Study project.
Is able to solve extreme control tasks of the complex electro-mechanical objects. - Practical examination task.
Evaluation criteria of study results
Answers to theoretical exam questions - 15%
Fulfillment of practical task of exam - 20%
Fulfillment of tests - 15%
Fulfillment of practical tasks - 20%
Fulfillment of study project - 30%
 
Course prerequisites Programming, electrical engineering.
Course planning
Part CP ECTS Hours Tests
Lectures Practical Lab. Test Exam Work
1 3.0 4.5 2.0 1.0 0.0 *
[Extended course information PDF]