National Institute of Technology Rourkela

राष्ट्रीय प्रौद्योगिकी संस्थान राउरकेला

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Syllabus

Course Details

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Subject {L-T-P / C} : EE6313 : Modelling of Dynamical Systems { 3-0-0 / 3}

Subject Nature : Theory

Coordinator : Rajiv Kumar Mishra

Syllabus

Module 1 :

Introduction (2 Lecture Hours)
Dynamical systems-classification, usages of modelling of dynamical systems, different modelling techniques

Module 2 :

Transfer function modelling of dynamical systems (6 Lecture Hours)
Transfer function modelling of mechanical systems, electrical systems, electromechanical systems, liquid level systems, biological systems, etc., transfer function modelling of MIMO systems

Module 3 :

State space modelling of dynamical systems (10 Lecture Hours)
State space representation-Linear, nonlinear, time-invariant, time-varying, SISO and MIMO systems, discrete-time systems, state space representation of mechanical systems, electrical systems, electromechanical systems, liquid level systems, biological systems, robot dynamics, etc., Introduction to modelling of descriptor systems and their properties.

Module 4 :

Energy-based modelling of dynamical systems (10 Lecture Hours)
The Lagrangian formalism- Elements of the Lagrangian Approach, Obtaining dynamical equations by Lagrangian method, The Principle of Least Action, Systems with two degrees of freedom, Lagrangian method applied to electrical circuits, Systems with external forces or e.m.fs, Systems with resistance or friction, Modelling of mutual inductances

Module 5 :

Introduction to Modelling of Network Systems (8 Lecture Hours)
Motivating examples of Network systems- social influence networks, wireless sensor networks, flocking model of animal behaviour, infectious diseases, algebraic graph theory, Laplacian matrix

Course Objective

1 .

Understand the fundamentals and classifications of dynamical systems.
2 .

Learn transfer function modelling for various physical systems.
3 .

Develop proficiency in state-space modelling of dynamical systems.
4 .

Apply Lagrangian formalism for energy-based system modelling.
5 .

Introduce the modelling of networked systems using graph theory.

Course Outcome

1 .

Classify and model different types of dynamical systems.
2 .

Develop transfer function models for physical systems.
3 .

Construct and analyse state-space representations.
4 .

Apply Lagrangian methods for system modelling.
5 .

Model and analyse networked systems using graph-theoretic tools.

Essential Reading

1 .

Katsuhiko Ogata, System Dynamics , Pearson Prentice Hall , Fourth Edition

2 .

Benjamin Kuo, Automatic Control Systems, McGraw Hill , Tenth Edition

Supplementary Reading

1 .

Norman S. Nise, Control Systems Engineering, Wiley , Seventh Edition

2 .

Joao Hespanha, Linear systems theory , Princeton Press , Second Edition

Journal and Conferences

1 .

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