Course detail
Theory of Dynamic Systems
FEKT-MTDSAcad. year: 2018/2019
System approach for solving technical problems. Cybernetics and system science .I/O and state space approach to the analysis and design of dynamic systems. Continuous,discrete, linear, non linear,time constant and time variable systems. Controlability and observability. State recontructors. Deterministic and stochastic systems. Algebraic approach. SISO and MIMO systems. Parameter estimation in closed loop. System robustness, sesitivity analysis, basics of algebraic approach towards controller design for dynamic systems.
Supervisor
Learning outcomes of the course unit
Ability to solve system problems by modern tools of system theory and science.
Prerequisites
The subject knowledge on the Bachelor´s degree level is requested.
Co-requisites
Not applicable.
Recommended optional programme components
Not applicable.
Recommended or required reading
Štecha,Havlena:Teorie dynamických systémů,ČVUT (CS)
Ogata:Modern Control Engineering,Prentice Hall (EN)
Beneš,J.:Teorie systémů,Academia. (CS)
Planned learning activities and teaching methods
Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations. Materials for lectures and exercises are available for students from web pages of the course. Students have to write a single project/assignment during the course.
Assesment methods and criteria linked to learning outcomes
30% from activities in numerical examples
70% final written exam
Language of instruction
Czech
Work placements
Not applicable.
Course curriculum
1. Dynamic system definition and divison.
2. Different types of system description: input output, transfer function, frequency response, polynomials.
3. State space description, state equations, their solution. Modeling of dynamical systems in Matlab Simulink.
4. Model realization: serial, parallel, direct programming.
5. Canonical forms: Frobenius, Jordan. Controlability, reachebility, observability, reconstructability of systems.
6. State estimators. Intelligent control algoritms.
7. Identification and approximation of dynamic systems. Discretization of continuous systems.
8. Hybrid systems solution. Optimal and suboptimal systems.
9. Multivariable feedback systems.
10. Adaptive control and intelligent controllers.
Aims
To present general system science and its application on dynamic systems.Applied system science.
Specification of controlled education, way of implementation and compensation for absences
The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.
Type of course unit
eLearning
eLearning: currently opened course