Course Title: Computational Modeling and Simulation II: Continuous Time Systems
Instructors: Dr. Hamid Vakilzadian and Dr. Dietmar Moeller
Office: 241 N WSEC
Telephone: Voice: (402) 472-1977 Fax: (402) 472-4732
Email: hvakilzadian@unl.edu
Time: 8:30–10 a.m. Wednesdays and Fridays
Office Hours: 12:30-1:30 PM WF
References:
· Mathematical and Computational Modeling and System Simulation: Fundamental and Case Studies by Dietmar Moeller, Springer Publ.
· Continuous Introduction to Transportation Analysis Modeling and Simulation – Computational Foundations and Multimodal Applications
by Dietmar Moeller, Springer Publ. 2014, and notes
· Continuous System Modeling, by Francois Cellier, Springer,
· 1991 Continuous System Simulation, by David Murray Smith,
· Springer, 1994 Notes and research papers
Prerequisite: Linear algebra and a programming language skill
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 constarints
- 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