Course detail

Theory of Dynamic Systems

FEKT-MTDSAcad. year: 2016/2017

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.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

doc. Ing. Petr Blaha, Ph.D.

Department

Department of Control and Instrumentation (UAMT)

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.

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

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.

Work placements

Not applicable.

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.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Beneš,J.:Teorie systémů,Academia. (CS)
Ogata:Modern Control Engineering,Prentice Hall (EN)
Štecha,Havlena:Teorie dynamických systémů,ČVUT (CS)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme EEKR-M Master's

    branch M-KAM , 1 year of study, winter semester, compulsory

  • Programme EEKR-M Master's

    branch M-KAM , 1 year of study, winter semester, compulsory

  • Programme EEKR-CZV lifelong learning

    branch EE-FLE , 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

doc. Ing. Petr Blaha, Ph.D.

Syllabus

System science,cybernetics,system approach.
Basic definitions,standard types of systems.
Real and anticipating systems.
I/O and state space approach.
Relationship between I/O and SSM.
Diagram of state variables,state matrix.
State matrix, stability and dynamic properties.
Direct,paralel and serial programing.Canonical forms.
Minimal form of SISO system.
Controlability and observability.
State and output feedback.State observers.
Decomposition and approximation of the systems.
Stochastic systems.

Fundamentals seminar

12 hod., compulsory

Teacher / Lecturer

Ing. Lukáš Pohl, Ph.D.

Syllabus

Block algebra and diagrams.I/O representation,state diagram.
Matrix representation.
Eigenvalues of state matrix,stability and dynamic properties.
State diagrams.
Minimal and canonical forms.
Aproximation and modeling of the systems.

Exercise in computer lab

12 hod., compulsory

Teacher / Lecturer

Ing. Libor Veselý, Ph.D.

Syllabus

I/O and state representation in MATLAB.
SIMULINK and its using for dynamic systems.
Toolboxes for dynamic systems in MATLAB.
Change of dynamic properties by state feedback.
Luenbergers obseŕver.
Decomposition of the system.