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Modelling and Simulation, 6 credits
Modellbygge och simulering, 6 hp
TSRT62
Main field of study
Electrical EngineeringCourse level
Second cycleCourse type
Programme courseExaminer
Claudio AltafiniDirector of studies or equivalent
Johan LöfbergEducation components
Preliminary scheduled hours: 58 hRecommended self-study hours: 102 h
ECV = Elective / Compulsory / Voluntary
Main field of study
Electrical EngineeringCourse level
Second cycleAdvancement level
A1XCourse offered for
- Computer Science and Engineering, M Sc in Engineering
- Industrial Engineering and Management - International, M Sc in Engineering
- Industrial Engineering and Management, M Sc in Engineering
- Information Technology, M Sc in Engineering
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
- Applied Physics and Electrical Engineering, M Sc in Engineering
- Chemical Biology
- Mechanical Engineering, M Sc in Engineering
- Engineering Biology, M Sc in Engineering
- Computer Science and Software Engineering, M Sc in Engineering
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Statistics, Automatic Control, Basic knowledge of electrical circuits and mechanics.Intended learning outcomes
The course should give knowledge about methods and principles for constructing mathematical models of dynamic systems (systems described by differential/difference equations), and about how properties of the models can be studied through simulation. Furthermore, the significance of dynamic properties and the limitation of static models will be studied. Students will be expected to be able to do the following after completing this course:
- Define, describe and apply basic concepts related to models, identification and simulation.
- Simplify a given model by using static relations, replacing variables by constants, using idealized assumptions and aggregation of states.
- Use scaling and dimension-free variables in order to simplify analysis of systems.
- Model (one-dimensional) mechanical, electrical, flow and thermal systems from balance and equilibrium equations. Furthermore, construct models including combinations of different domains, in DAE form and (when possible) state-space form.
- Construct bond graphs for appropriate systems from the class mentioned above. Simplify and analyze bond graphs with respect to causality. From a given bond graph, compute a corresponding state-space model.
- Compute the index for a given DAE and describe the different standard forms for linear DAE:s.
- Model and simulate (one-dimensional) mechanical and electrical systems in Simulink and Modelica, and write simple Modelica objects in code.
- Use system identification to construct a model of a real system, through appropriate choices of experiment design, post-processing of data, model structure, and careful validation.
- Compute asymptotic bias and variance properties for a given linear system identification problem.
- Describe nonlinear graybox models, local models, local linear models and nonlinear regression models (in particular neural networks), and estimate models of these types for very simple cases.
- Determine whether a given simulation method is implicit or explicit and how many steps it contains. Compute the local error and stability region for simple simulation methods.
- Produce a well-written, informative lab report.
Course content
Models and modeling: Different types of models. Continuous and discrete time models. Differential and difference equations. State-space descriptions. Principles for model building, starting from physical relations. Balance and state equations. Simplification of models. Analogies between different physical domains. Bond graphs. Differential algebraic models. Object-oriented modeling. Models with disturbances. Black-box models.
Identification: Transient-response, frequency, correlation, and spectral analysis. Parameter estimation for linear and nonlinear dynamic models. System identification as a model building tool. Model validation.
Simulation: Methods for state-space and differential algebraic models. Numerical properties and stability. The simulation languages Simulink and Modelica.
Teaching and working methods
The course consists of lectures, lessons and laboratory work.
Examination
| LAB1 | Laboratory Work | 1.5 credits | U, G |
| DAT1 | Computer Examination | 4.5 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Institutionen för systemteknikDirector of Studies or equivalent
Johan LöfbergExaminer
Claudio AltafiniCourse website and other links
http://www.control.isy.liu.se/student/tsrt62/Education components
Preliminary scheduled hours: 58 hRecommended self-study hours: 102 h
Course literature
Additional literature
Books
- Ljung, L., Glad. T, (2004) Modellbygge och simulering andra upplagan
Compendia
| Code | Name | Scope | Grading scale |
|---|---|---|---|
| LAB1 | Laboratory Work | 1.5 credits | U, G |
| DAT1 | Computer Examination | 4.5 credits | U, 3, 4, 5 |
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Additional literature
Books
Ljung, L., Glad. T, (2004) Modellbygge och simulering andra upplagan
Compendia
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
|
|
X
|
DAT1
LAB1
|
||
| 1.2 Fundamental engineering knowledge (G1X level) |
|
X
|
X
|
DAT1
LAB1
|
||
| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
X
|
X
|
|
DAT1
LAB1
|
||
| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
|
|
|
|||
| 1.5 Insight into current research and development work |
|
|
|
|||
| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
|
X
|
|
LAB1
|
||
| 2.2 Experimentation, investigation, and knowledge discovery |
|
X
|
X
|
LAB1
|
||
| 2.3 System thinking |
|
X
|
X
|
DAT1
LAB1
|
||
| 2.4 Attitudes, thought, and learning |
|
|
X
|
DAT1
LAB1
|
||
| 2.5 Ethics, equity, and other responsibilities |
|
|
|
|||
| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
|
|
X
|
LAB1
|
||
| 3.2 Communications |
|
|
X
|
LAB1
|
||
| 3.3 Communication in foreign languages |
|
|
|
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
X
|
|
|
|||
| 4.2 Enterprise and business context |
|
|
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| 4.3 Conceiving, system engineering and management |
X
|
X
|
|
DAT1
LAB1
|
||
| 4.4 Designing |
|
|
|
|||
| 4.5 Implementing |
X
|
X
|
|
LAB1
|
||
| 4.6 Operating |
|
|
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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