Lecturer(s)
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Course content
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1. Transfer function: poles and zeros. State-space description, linearization. 2. Parametric and non-parametric identification, design of identification measurement. 3. Parameter estimation of the transfer functions with the least squares method and chosen structure based on the input/output measuring. Model order reduction, model verification. 4. Z-transformation, discrete system description, ARX model. 5. Analysis of the real system in the frequency domain. 6. The root locus of a feedback system: open and closed loop. Guideline for sketching a root locus. 7. Controller structures and design with root locus. 8. Controller tuning in the frequency domain. Simplified forms of the Nyquist criterion. Gain and phase margin. 9. Enhancements to single-loop PID feedback control. Internal model control. 10. State-space representation of systems. 11. Structure of state feedback control, design of state feedback matrix using the pole placement. 12. State feedback control with an integrator. State observer. 13. Mathematical description of MIMO systems, transfer function matrix, gain matrix. 14. MIMO system control, decomposition.
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Learning activities and teaching methods
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Laboratory work, Lecture, Practicum
- Semestral paper
- 44 hours per semester
- Preparation for credit
- 10 hours per semester
- Preparation for exam
- 40 hours per semester
- Class attendance
- 56 hours per semester
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Learning outcomes
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This subject offers a comprehensive overview of control systems with accent on an appropriate balance between theoretical concepts and engineering practice in analysis, synthesis and identification of linear dynamic systems. The subject focuses on empirical identification, single loop control design method, problems of optimal PID control strategy and application of frequency domain methods. The important part consists of solving complicated control loops as feed forward, cascade, multiloop pairing and fundamental approach to state variable control. Theoretical and practical lessons involve utilization of MATLAB software tools. The implementation of the theory will be carried out on physical real models with industrial equipment in the Control laboratory. Extensive computer assisted laboratory exercises cover such tasks as rotation speed control of a system with DC-motor, tachometer and elastic clutch with a load, water temperature control of a circulation water boiler heater, level control, temperature control of air flow and others.
The students will acquire good knowledge of practical parameter estimation for determined model structure, analysis and synthesis of dynamic systems, PID controller tuning, practical design of industrial control systems, and review of Multi Input Multi Output systems and basic knowledge of state controller design. They will become familiar with implementation of control algorithms using modern software tools. Web based interactive modules assist student self study and help prepare practical experimentation. The practical lessons use software tools and utilizations of MATLAB.
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Prerequisites
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The knowledge of basic automatic control theory, PIC controllers, signal analysis, and Laplace transform are necessary.
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Assessment methods and criteria
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Combined examination, Oral exam, Written exam, Practical demonstration of acquired skills
Requirements for getting a credit are activity at the practicals /seminars and presentation of reports. Examination is of the written and oral forms.
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Recommended literature
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Golnaraghi, F, Kuo, B.C. Automatic Control Systems. McGraw Hill, 2017. ISBN 978-1259643835.
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Isermann, R.:. Mechatronics Systems. Fundamentals.. Springer, London., 2003. ISBN ISBN 1852336935.
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Modrlák, O., Hubka, L. Automatické řízení. Liberec, 2012. ISBN 9788073728502.
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NOSKIEVIČ,P.:. Modelování a identifikace systémů.. MONTANEX a.s., Ostrava., 1999.
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Shinskey, F. G. Process Control Systems. Application, Design, and Tuning. Mc Graw Hill. ISBN 0-07-057101-5.
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