Course Descriptions and Syllabi

Spring 2004

 

 

Textbook: Theory of Modeling and Simulation, B.P. Zeigler, H. Praehofer, T.G. Kim, Academic Press, San Diego, 2000.

We will also use additional material to cover cellular automata, bond graph modeling, and hybrid systems modeling. Copies of the book chapters and papers used will be provided to all students.

Course Objectives: The objective of this course is to cover the general theory of modeling and simulation of a variety of systems: physical processes, computer systems, biological systems and natural processes, and manufacturing processes. The goal is to focus on the principles of discrete-event, continuous, and hybrid system modeling, and use these methodologies to construct models of a number of realistic systems. Computational issues and analysis techniques associated with the modeling paradigms will also be studied. We will look at and develop simulation algorithms, which we will implement in Matlab using Simulink and Stateflow techniques.

 

The grades for the course will be based on a set of Matlab-based assignments and a class project that students can work on in pairs. Students are permitted to use different modeling and simulation environments for their project work, and apply the techniques learnt to their particular domain of interest.

 

Topics covered will include Introduction to Systems Modeling Concepts, Modeling formalisms and their simulators, Cellular automata, Discrete event systems modeling, Continuous system modeling, Bond Graph approach to modeling physical systems, Stochastic systems, and Hybrid (continuous + discrete) systems. If time permits, we will cover some advanced topics, such as Abstraction models, Distributed systems, and verification and validation mechanisms.

 

Who should take this course? This course should be of interest to students in Computer Science, Computer Engineering, and other engineering disciplines. This course will not delve into the theory of modeling nor will get into the details of numerical methods that are used in simulation algorithms. Instead we will study modeling paradigms, and how they may be employed for building models of real (or realistic) systems. The focus will be on model building and interpreting and analyzing results of simulation runs with the constructed models. The prevalence of embedded systems requires both Computer science and engineering students to cross the traditional discrete and continuous boundaries that they work in, and study modeling and simulation methodologies that combine the two paradigms.

 

Please contact the instructor if you have additional questions.

Topics Covered: Spring 2004.

Jan-15-04	Introduction to Modeling and Simulation
Jan-20-04	System Modeling Framework and Specifications
Jan-22-04	Discrete Time Models + Cellular Automata
Jan-27-04	Cellular Automata + Game of Life
Jan-29-04	Cellular Automata (2D) + Discrete Time Simulations
Feb-03-04	Differential Equations + Discrete Event Systems
Feb-05-04	Introduction to Simulink modeling in Matlab
Feb-10-04	Discrete Event System Specifications (DEVS)
Feb-12-04	Modeling and Simulation of Supply Networks
Feb-17-04	Modeling Discrete Event Systems
Feb-19-04	Continuous System Modeling: Introduction to Bond Graphs
Feb-24-04	Modeling with Bond Graphs -- continued
Feb-26-04	Building Bond Graph Models + Causality Assignment
Mar-02-04	Causality Assignment + Equation Generation with Bond Graphs
Mar-04-04	Building Simulink models from Bond Graphs
Mar-09-04	Spring Break -- no class
Mar-11-04	Spring Break -- no class
Mar-16-04	No class -- work on project and HW
Mar-18-04	Introduction to Stateflow
Mar-23-04	DES and the DEVS Formalism
Mar-25-04	The DEVS Formulation
Mar-30-04	Coupled DEVS models
Apr-01-04	Discussion of Stateflow + Project Presentations
Apr-06-04	Discussion of Stateflow + Project Presentations
Apr-08-04	Project Presentations
Apr-13-04	Monte Carlo and Stochastic Simulation
Apr-15-04	Monte Carlo Simulation: pdfs
Apr-20-04	Monte Carlo + Stochastic simulation
Apr-22-04	Analyzing Input and Output: Stochastic Simulations
Apr-27-04	Review Stochastic Simulations + Hybrid Modeling + Course Review
May-01-04	Final Project Presentations -- Group 1
May-06-04	Final Project Presentations -- Group 2