Systems and Models

The course is a substitute for:

Systems and Models (X35SAM)

Lecturer:

Tutor:

Supervisor:

Department of Control Engineering

Synopsis:

Dynamical systems modeling and identification of deterministic models assumed to be used in simulation, analysis and control system design namely in automation. Bond Graph systematic modeling of mechanical, hydraulic, pneumatic, electrical and thermal systems and their assemblies. State space and Input/Output formal models, e.g. transfer functions, differential equations, frequency and step response. Continuous and discrete time models. Spectral analysis and least squares methods for nonparametric and ARX model identification.

Requirements:

Syllabus of lectures:

1. Systems, control systems modeling

2. Input-output models of continuous time, transfer functions, analysis

3. State space continuous time models, model analysis, linearization

4. Analytical and numerical methods for solving state space equations

5. State space and input-output discrete time models, linear model analysis

6. Impulse, step and frequency response characteristics

7. Sampling of continuous signals and system, sampling rate selection

8. Formal model conversion and model order reduction

9. Modeling of physical systems by Bond Graphs

10. Modeling of electromechanical, hydraulic and pneumatic systems

11. Modeling of sensors, amplifiers and power transducers

12. Thermal systems modeling

13. Signal based system identification, spectral analysis and least squares methods

14. Design of experiment for identification of ARX model parameters from data

Syllabus of tutorials:

1. Introduction to laboratory equipment, scale models of physical systems

2. MATLAB programming package - elementary functions

3. SIMULINK system simulation package

4. Control and Signal Toolboxes for MATLAB

5. Data acquisition and real-time signal processing - Real Time Toolbox

6. Laboratory project 1: modeling, parameter identification by direct measurement

7. Simulation of nonlinear and linearized continuous time model in SIMULINK

8. Simulation of linearized model on an analog computer

9. Bond Graph modeling, Z-transform, discrete systems descriptions

10. TEST, continuous to discrete time model conversion, individual project definition

11. Laboratory project 2: modeling, parameter identification by direct measurement

12. Simulation of nonlinear and linearized continuous time model in SIMULINK

13. ARX model parameters identification by least squares

14. Discussion on laboratory project results

Study Objective:

Study materials:

[1] Karnoop, D.C., Margolis, D.L., Rosenberg, R.C.: System Dynamics: A Unified Approach. John Wiley,New York 1990

[2] Franklin, G.F., Powell, J.D., Emami-Naeini, A.: Feedback Control of Dynamic Systems. Addison-Wesley, New York 1995

[3] Astrom, K.J., Wittenmark, B.: Computer Controlled Systems - Theory and Design. Prentice Hall, Englewood Cliffs, 1990

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Kybernetika a měření-bakalářský blok (compulsory course)
• Kybernetika a měření-bakalářský blok (compulsory course)