SylabUZ
| Course name | Advanced control systems and computer networks |
| Course ID | 06.2-WE-ELEKTD-ACSandCN- SPiE-Er |
| Faculty | Faculty of Computer Science, Electrical Engineering and Automatics |
| Field of study | Electrical Engineering |
| Education profile | academic |
| Level of studies | Second-cycle Erasmus programme |
| Beginning semester | winter term 2017/2018 |
| Semester | 2 |
| ECTS credits to win | 6 |
| Course type | optional |
| Teaching language | english |
| Author of syllabus |
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| The class form | Hours per semester (full-time) | Hours per week (full-time) | Hours per semester (part-time) | Hours per week (part-time) | Form of assignment |
| Lecture | 30 | 2 | - | - | Credit with grade |
| Laboratory | 15 | 1 | - | - | Credit with grade |
| Project | 15 | 1 | - | - | Credit with grade |
- familiarize students with control techniques of bases power converters
- familiarize students with bases of control with help of neural networks
- shaping basic skills for selection and adjust of parameters under using of standard control strategy of power converters
- formation among the students understanding of control problems, monitoring and diagnostic of distributed systems
Selected issues of circuit theory I and II
Voltage regulation techniques. Method of identification of basic harmonic. Integrated methods. Momentary power theory p-q – bases. Momentary power theory in orthogonal coordinates. Control techniques of power flow. Variable structure control. Phase space method. Methods of variable structure construction. Idea of generation of induced motions. Conditions of existence of sliding mode.
Neural networks. Unidirectional networks. Recurrent networks. Teaching neural networks methods. Backpropagation algorithm. Neural networks in adaptive system. Neural control system.
Fuzzy control. Fuzzy control models. Fuzzy control in industry. Systems based on knowledge about processes. Controller based on knowledge (KBC). Knowledge presentation in controller KBC. Adaptive control systems. Adaptive mechanism. Operation estimation.
Adaptive control systems for static object. Self-organized regulator. Regulator based on model. Optimal control. Dynamical optimization conception. The principle of maximum. Control at minimum expense. Technical implementation of the optimum control system.
Computer Networks. OSI model. Local computer networks. Equipment and signals of the first layer of the OSI model. Media, connections, and collisions in the first layer of the OSI model. The second layer of the OSI model - the basics. Secondary OSI model technologies. Design and documentation of computer networks. Structural cabling. Addressing on computer networks. Routing and routed protocols. OSI model transport layer. Session layer of the OSI model. Presentation layer of the OSI model. Application layer model OSI.
Lecture, laboratory exercises, project
| Outcome description | Outcome symbols | Methods of verification | The class form |
Lecture – obtaining a positive grade in written exam.
Laboratory – the main condition to get a pass are sufficient marks for all exercises and tests conducted during the semester.
Calculation of the final grade: lecture 40% + laboratory 30% + project 30%
1. Kevin Gurney. An Introduction to Neural Networks. CRC Press, 2003 - 234
2. Hingorani N., Gyugyi L.: Understanding FACTS. Concepts and Technology of Flexible AC Transmission Systems, IEEE Press, New York, 2000.
3. Song Y., Johns A.: Flexible AC Transmission Systems (FACTS), IEE Power and Energy Series 30, TJ International Ltd, Padstow, Cornwall, 1999.
1. Jeff Doyle, Jennifer DeHaven Carroll. Routing TCP/IP, Volume 1, 2nd Edition. Cisco Press. 2005
2. Vito Amato; Wayne Lewis. Cisco Networking Academy Program: First-Year Companion Guide. Cisco Systems, 2000.
Modified by dr hab. inż. Radosław Kłosiński, prof. UZ (last modification: 27-04-2017 08:36)
