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Vastavalt doktoritöö teemale juhendaja soovitatud eripeatükid automaatjuhtimise teooriast. Kursus sisaldab probleemloenguid ja modelleerimiskeskkonna MATLAB/SIMULINK kasutamisel põhinevaid harjutusi.

Control of systems. Control goals. Automatic control. Architecture of control systems. Feedforward and feedback. Disturbances. Mathematical modelling of systems as precondition to control system design. Classification of control systems: Fixed-parameter systems, Adaptive systems, Intelligent (self-learning) systems. (I) Dynamical system models ? linear and non-linear models, continuous and discrete models. Analytical and non-analytical models. (II) Main control methodologies ? model-based control, multivariable control, predictive control, robust control, adaptive control, intelligent control. (III) Multidimensional control ? multirate modeling and control of systems (IV) Robust systems - uncertainty, stability region, stability margins, robust control. (V) Adaptive control - parameter adaptive and model reference adaptive control systems, stability analysis. (VI) Applications of fuzzy logic and artificial neural networks in dynamic system control. Non-linear control of systems. Learning algorithms. Integrated control methods. The course includes problem-oriented lectures, practical works in MATLAB/SIMULINK and seminars. Different control problems are analyzed with several control approaches proposed and solutions simulated, talks are given.

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IEEE Transactions: Automatic Control; Fuzzy Systems; Neural Networks; Robotics; Automation Science and Engineering; Systems, Man, Cybernetics;
International Journal of Control; IEE Proceedings: Control Theory and Applications; Aström K.J., B.Wittenmark “ Computer-Controlled Systems: Theory and Design”, Prentice Hall, 1997; Nauck D, F.Klawonn, R.Kruse “Foundations on Neuro-Fuzzy Systems”, Wiley, 1997; Huang, S., Tan, K. K., Tang, K. Z. Neural network control : theory and applications, Baldock :

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