SylabUZ
| Course name | Advanced control methods |
| Course ID | 06.0--AutD-ZMS-Er |
| Faculty | Faculty of Computer Science, Electrical Engineering and Automatics |
| Field of study | Automatic Control and Robotics / Computer Control Systems |
| Education profile | academic |
| Level of studies | Second-cycle Erasmus programme |
| Beginning semester | winter term 2020/2021 |
| Semester | 2 |
| ECTS credits to win | 5 |
| Course type | obligatory |
| 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 |
| Laboratory | 30 | 2 | - | - | Credit with grade |
| Lecture | 30 | 2 | - | - | Exam |
1. To familiarize with modern methods of designing control systems based on optimization methods.
2. Develop understanding of the model uncertainty and external disturbances impacts, and how to minimize them.
3. To familiarize with methods of formulating and solving synthesis problems of static and dynamic controllers using linear matrix inequalities.
Control Theory. Optimization methods.
Application of linear matrix inequalities in control theory. Stability and stabilization problems in the form of linear matrix inequalities. Synthesis of state feedback controllers under multi-criteria constrains.
Analysis of control systems robustness. Disturbance attenuation using H2 and Hinf norms of systems. Design of static state and output controllers by linear matrix inequality techniques. Extending the conditions to the case of model uncertainty and external disturbances. Controller design with an additional integrator.
Designing of dynamic controllers. Formulating the design as the optimization problem. Extensions of design procedures to cases of model parameter uncertainties and external disturbances. Minimization of H2 and Hinf norms of systems.
Designing discrete controllers for discrete plants using optimization methods. Static and dynamic controllers for discrete plants.
lecture: classical lecture,
laboratory: laboratory exercises, projects carried out in two-person group.
| Outcome description | Outcome symbols | Methods of verification | The class form |
lecture: final test.
laboratory: the passing condition is to obtain positive marks from all laboratory exercises and projects to be planned during the semester as well as give back all reports from laboratory exercises.
Final grade = lecture: 50% + laboratory: 50%
1. Wojciech Koziński. Projektowanie regulatorów. Wybrane metody klasyczne i optymalizacyjne. Wydawnictwo: OWPW.2004
2. S.Boyd, L. ElGhaoui, E. Feron, V. Balakrishnan. Linear Matrix Inequalities in System and Control Theory. SIAM, 1994.
3. L. El-Ghaoui, S.Niculescu. Advances In Linear Matrix Inequality Methods In Control. SIAM 2000.
1.R.C. Dorf, R.H. Bishop, Modern control system, Pearson Education, Inc. London, 2008.
2.R.F. Stengel, Optimal Control and Estimation, Dover Publications, Mineola, N.Y., 1994
Modified by dr hab. inż. Wojciech Paszke, prof. UZ (last modification: 29-04-2020 10:31)
