UNIVERSITY OF NEBRASKA-LINCOLN
Department of Electrical and Computer Engineering
in Collaboration with
Technical University of Clausthal, Germany
ECEN-498/898 Fall, 2019
Course Title: Computational Modeling and Simulation II: Continuous Time Systems
Instructors: Dr. Hamid Vakilzadian
Office: 241 N WSEC
Telephone: Voice: (402) 472-1977 Fax: (402) 472-4732
Email: hvakilzadian@unl.edu
Time: 8:15 - 9:45 am Wednesdays and Fridays
Office Hours: 10:00 -11:00 am MWF
References:
1. Mathematical and Computational Modeling and System Simulation: Fundamental and Case Studies by Dietmar Moeller, Springer Publ. 2003
2. C. Moler, Numerical Computing with MATLAB, available at http://www.mathworks.com/moler/chapters.html (see that webpage for use restrictions)
3. Supplemental notes and research papers
Prerequisite: Linear Algebra and A Programming Language skill (Mathlab is preferred)
The course will cover:
1. Intro. to Systems
Classification, measurement, complexity, attributes, etc.
2. Intro. to Modeling
Modeling techniques, type of models, static/dynamic/physical/mathematical, etc.
3. Representation of a Model
Representation of a System using Differential Equations
Existence and Uniqueness of Solutions of Differential Equations
Controllability, Observability, and Identifiability
Linear State-Equation Models (1st, 2nd, multi)
4. Simulation Software
Simulation packages; desired features; examples
5. Integration Algorithms
Single step, multi-step, stiff
Accuracy and stability of integration algorithms
6. Parameter Identification of Continuous Systems
Least Square Method (Output-Error, Equation-Error)
Consistency of Parameter Estimates
Identifiability
Sensitivity Analysis
Error-Function Minimization by Gradient Methods and Direct Search Methods
7. Verification and Validation of Simulation Models
a. Verification of Simulation Models
b. Validation of Model Assumptions
c. Techniques for Increasing Model Validity
8. Project
Project work in an area of concentration chosen by the students’ interest
At the end of this course, students will be able to:
- Understand the core principles behind Computational Modeling and Simulation (CMS)
- Understand abstraction of systems being analyzed by CMS
- Learn how to develop models for application specific domains w.r.t constraints
- Verify and validate models of appropriate scale
- Understand the required semantics of a model for testing
- Develop a problem solving oriented competence in CMS
For questions/information, please contact
Dr. Vakilzadian @ hvakilzadian@unl.edu