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Jožef Stefan
International
Postgraduate School

Jamova 39
SI-1000 Ljubljana
Slovenia

Phone: +386 1 477 31 00
Fax: +386 1 477 31 10
Email: info@mps.si

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Course Description

Modern Control Technologies

Program

Information and Communication Technologies, second-level study programme

Lecturers:

prof. dr. Đani Juričić
doc. dr. Damir Vrančić

Goals:

Control is a " hidden" technology which ensures efficient and safe operation of systems in accordance with the requirements. The aim of the course is to acquiaint students with basic concepts and to present a number of state-of-the-art procedures for solving complex control problems. The course will provide a framework for understanding control technology in the form of a life cycle model which interconnects practical requirements, design and implementation in a concise manner. Procedures for planning self- adjusting and adaptive systems, non-linear control systems and supervision systems will be presented in greater detail. Practical examples highlighting the basic concepts will be provided as well.

Content:

1) Introduction
Life-cycle basics: technical implementation phases, the analysis of functional requirements (what the system should do), specification, design, implementation and maintenance; non-technical aspects (man-machine interface, technoeconomics, social aspects).

2) Basic building blocks of state-of-the-art control technologies
Review of sensors, actuators, signal conditioning and transmission; sampling.

3) Modern concepts of control design in time space
Basic concepts: controllability; identifiability; optimal state regulator; self-adjusting and adaptive regulators; examples from industry.

4) Intelligent supervisory systems
Reliability, efficiency and quality requirements; early error detection procedures based on models; application of signal processing methods; fault isolation by using approximate reasoning; examples of industrial applications.

5) Model based control
Practical relevance of state estimation of dynamic systems; Kalman filter; extended Kalman filter; " bootstrap" procedures for state estimation of nonlinear dynamic systems; examples of application in forecasting and navigation; predictive control

6) Predictive control
Basic concepts; solution of the quadratic cost function; tuning; robustness; application.

Course literature:

• G.C. Goodwin, S.F. Graebe and M.E. Salgado (2003). Control System Design. McGraw Hill, New Jersey.
• B. Kouvaritakis and M. Cannon (2001). Nonlinear Predictive Control: Theory and Practice. The Institution of Electrical Engineers, London.
• J. M. Maciejowski (2002). Predictive Control with Constraints. Prentice-Hall.
• M. Blanke, M. Kinnaert, J. Lunze and M. Staroswiecki (2003). Diagnosis and Fault-Tolerant Control. Springer-Verlag. Berlin.
• S. Strmčnik (Urednik) (1998). Celostni Pristop k Računalniškemu Vodenju Procesov. Založba FE in FRI. Univerza v Ljubljani, Ljubljana.
• C.F. Lin (1994). Advanced Cntrol Systems Design. Prentice-Hall, Englewood Cloffs N.J.
• E.L. Russell, L. H. Chiang and R. Braatz (2000). Data-Driven Techniques for Fault Detection and Diagnosis in Cemical Processes. Springer, London.
• D. Kaplan, L. Glass (1995). Understanding Nonlinear Dynamics. Springer, New York.

Significant publications and references:

• Mileva-Boshkoska, B., Boškoski, P., Debenjak, A., Juričić, Đ. Dependence among complex random variables as a fuel cell condition indicator. Journal of Power Sources, [in press], 26 str., 2015.
• Debenjak, A., Boškoski, P., Musizza, B., Petrovčič, J., Juričić, Đ. Fast measurement of proton exchange membrane fuel cell impedance based on pseudo-random binary sequence perturbation signals and continuous wavelet transform. Journal of Power Sources, 254, 112-118, 2014.
• Boškoski, P., Gašperin, M., Petelin, D., Juričić, Đ. Bearing fault prognostics using Rényi entropy based features and Gaussian process models. Mechanical Ssystems and Signal Processing, 11 str.,2014
• Moura O. P. B., Vrančić, D., Boaventura C.J., Solteiro P. E.J. Teaching particle swarm optimization through an open-loop system identification project. Computer Applications in Engineering Education, 22(2), 227-237, 2014
• Mileva-Boshkoska, B., Boškoski, P., Debenjak, A., Juričić, Đ. Dependence among complex random variables as a fuel cell condition indicator. Journal of Power Sources, [in press], 26 str., 2015.
• Debenjak, A., Boškoski, P., Musizza, B., Petrovčič, J., Juričić, Đ. Fast measurement of proton exchange membrane fuel cell impedance based on pseudo-random binary sequence perturbation signals and continuous wavelet transform. Journal of Power Sources, 254, 112-118, 2014.
• Boškoski, P., Gašperin, M., Petelin, D., Juričić, Đ. Bearing fault prognostics using Rényi entropy based features and Gaussian process models. Mechanical Ssystems and Signal Processing, 11 str.,2014
• Moura O. P. B., Vrančić, D., Boaventura C.J., Solteiro P. E.J. Teaching particle swarm optimization through an open-loop system identification project. Computer Applications in Engineering Education, 22(2), 227-237, 2014

Examination:

Seminar and oral exam (100%)

Students obligations:

Seminar and oral exam.

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