700.383 (17S) LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing

Sommersemester 2017

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Überblick

Lehrende/r
LV-Titel englisch
LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing
LV-Art
Kurs (prüfungsimmanente LV )
Semesterstunde/n
2.0
ECTS-Anrechungspunkte
3.0
Anmeldungen
13 Anzahl der tatsächlich angemeldeten Studierenden
Organisationseinheit
Unterrichtssprache
es wurde keine Unterrichtssprache angegeben
LV-Beginn
01.03.2017
eLearning
zum Moodle-Kurs

Zeit und Ort

Tag von - bis Raum Details
Do, 02.03.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 09.03.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 16.03.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 23.03.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 30.03.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 06.04.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 27.04.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 04.05.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 11.05.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 18.05.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 01.06.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 08.06.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 22.06.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Do, 29.06.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich

LV-Beschreibung

Intendierte Lernergebnisse

This lecture is mainly focused on the numerical simulation (using MATLAB/SIMULINK) and ANALOG COMPUTING (using electronic circuits) of several mathematical models of Nonlinear dynamical systems (NDS), which are generally expressed in form of ordinary differential equations ODES and/or partial differential equations PDES (e.g. case of continuous NDS), or in form of sets of coupled algebraic equations (e.g. case of discrete NDS). The ODEs and PDEs at stake are identical to those used/considered in the theoretical part of this lecture (see LV 700.371 (17S)). All ODEs and PDEs under investigation are selected in the field on engineering (e.g. in Mechanics, Electro-mechanics, Control systems, Electronics, Transportation, Telematics, etc.) as typical models of the dynamics of specific systems, scenarios, or phenomena. For each of the ODEs and PDEs models, the numerical (MATLAB/SIMULINK) and experimental (ANALOG COMPUTING) studies are considered simultaneously and several numerical and experimental methods are proposed. Using these methods, numerical and experimental solutions of the mathematical models are obtained.  The proof of concepts is based on the comparison of results obtained by the three methods: the analytical methods presented in LV 700.371 (17S) Nonlinear Dynamics -- Modeling, Simulation and Neuro-Computing, and the numerical, and experimental methods presented in this Lecture (LV 700.383 (17S) LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing). The Lecture also proposes numerical methods for solving mathematical models of discrete nonlinear dynamical systems expressed in form of coupled algebraic equations. Finally numerical algorithms are developed for the analysis of oscillatory states/behavior, equilibrium state, stability, bifurcation, and chaos detection.

The general expectation regarding the knowledge to be provided/acquired is as follows:

  • Mastering of numerical methods for solving linear and nonlinear ODEs and PDEs used as mathematical models of continuous nonlinear dynamical systems (CNDS).
  • Mastering of the analog computing technique (i.e. use of electronic circuits) for solving nonlinear ODEs.   
  • Mastering of numerical methods for solving DNDS (discrete nonlinear dynamical systems).
  • Mastering of numerical methods for the stability analysis of both DNDS (discrete nonlinear dynamical systems) and CNDS (continuous nonlinear dynamical systems).
  • Mastering of numerical algorithms/codes for the detection of chaotic dynamics in NDS (nonlinear dynamical systems).
  • Mastering of numerical algorithms/codes for bifurcation analysis in NDS.
  • Mastering of the design and implementation of electronic circuits for solving nonlinear ordinary differential equations (ODEs) and Partial differential equations (PDEs).

Very Important: Many projects will be proposed in accordance to all seven points above in order to check whether the main/key objectives of this Lecture (LV 700.383 (17S) are fulfilled.

Literatur

[1]- Peter J. Olver, “Introduction to Partial Differential Equations,” Springer, New York, 2016

[2]-  William E. Schiesser, and Graham W. Griffiths “A Compendium of Partial Differential Equation Models: Method of Lines Analysis with Matlab,” Cambridge University Press, 2006

[3]- Bernard Zeigler, Tag Kim, and Herbert Praehofer, “Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems,” Academic Press, USA, 2000

[4]- Michael Schäfer, “Computational Engineering — Introduction to Numerical Methods,” Springer, 2006

[5]- L.O. Chua, T. Roska, “Cellular Neural Networks and Visual Computing: Foundations and Applications,” Cambridge University Press, 2002.

Prüfungsinformationen

Beurteilungsschema

Note/Grade Benotungsschema

Position im Curriculum

  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Autonomous Systems and Robotics: Advanced (ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (siehe Anhang 3) ( 0.0h VK, VO / 30.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Autonomous Systems and Robotics (WI) (Wahlfach)
      • Wahl aus dem LV-Katalog (siehe Anhang 3) ( 0.0h VK, VO / 30.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Free Electives (Freifach)
      • Free Electives ( 0.0h XX / 6.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information Technology (SKZ: 489, Version: 06W.3)
    • Fach: Technischer Schwerpunkt (Intelligent Transportation Systems) (Pflichtfach)
      • 1.4-1.5 Kurs oder Labor ( 4.0h KU / 6.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information Technology (SKZ: 489, Version: 06W.3)
    • Fach: Technische Ergänzung I (Pflichtfach)
      • 2.3 Vorlesung mit Kurs oder Seminar ( 2.0h VK/SE / 4.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information Technology (SKZ: 489, Version: 06W.3)
    • Fach: Technische Ergänzung II (Pflichtfach)
      • 3.4-3.5 Kurs oder Labor ( 4.0h KU / 6.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information Technology (SKZ: 489, Version: 06W.3)
    • Fach: Informationstechnische Grundlagen (Pflichtfach)
      • 3.1'-3.3' Vorlesung und Kurs ( 12.0h VO, KU / 18.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)
  • Masterstudium Information Technology (SKZ: 489, Version: 06W.3)
    • Fach: Research Track (Methodischer Schwerpunkt) (Pflichtfach)
      • 4.2'-4.3' Theoretisch-Methodische Lehrveranstaltung I/II ( 0.0h VO/VK/VS/KU/PS / 6.0 ECTS)
        • 700.383 LAB on Nonlinear Dynamics - Modeling, Simulation and Neuro-Computing (2.0h KS / 3.0 ECTS)

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