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Lecturer(s)
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Dušek František, doc. Ing. CSc.
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Course content
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Adaptive control of single-input single-output systems. Model Reference Control, Gain Scheduling, suboptimal control with on-line identification. Linear Quadratic (Gaussian) control and state estimation. Control of multi-input multi-output linear systems. Predictive Control based on state space model.
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Learning activities and teaching methods
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Work with text (with textbook, with book), Methods of individual activities
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Learning outcomes
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The aim is to inform students about advanced methods of control design of linear dynamic continuous systems in discrete-time area. Attention is paid to next areas: adaptive control of single-input single-output systems (Model Reference Control, suboptimal control with on-line identification), stochastic systems, Linear Quadratic (Gaussian) control and state estimation, predictive control of multi-input multi-output systems
Students get knowledge about design of adaptive control and MIMO linear systems control.
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Prerequisites
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Knowledge of differential calculus, linear algebra and basic of process control is needed. Knowledge of MATLAB/SIMULINK is needed.
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Assessment methods and criteria
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Oral examination, Home assignment evaluation
Working-out of dated up work Exam
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Recommended literature
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ASTRÖM, K. J.; WITTENMARK, B. Adaptive Control. Addison-Wesley Publishing, 1995.
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CAMACHO, E. F., BORDONS, C. Model Predictive Control. Springer Verlag, 1999..
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HAVLENA, V.; ŠTECHA, J. Moderní teorie řízení. Vydavatelství ČVUT, Praha, 2000.
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Maciejowski, J. M. Predictive Control with Constrains. 2002, Pearson Education Ltd., Essex.
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OGATA, K. Discrete-Time Control Systems. Prentice Hall, 1995..
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OGATA, K. Modern Control Engineering. Prentice Hall, 1990..
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