JModelica.org
User Guide

Version 1.15

2014-12-12


Acknowledgements

This document is produced with DocBook 5 using XMLMind XML Editor for authoring, Norman Walsh's XSL stylesheets and a GNOME xsltproc + Apache fop toolchain. Math contents is converted from LaTeX using the TeX/LaTeX to MathML Online Translator by the Ontario Research Centre for Computer Algebra and processed by JEuclid.

Table of Contents

1. Introduction
1. About JModelica.org
2. Mission Statement
3. Technology
4. Architecture
5. Extensibility
2. Installation
1. Supported platforms
2. Installation on Windows
2.1. Dependencies
2.2. Installation
2.3. Verifying the installation
2.4. Compilation from sources
3. Installation on Linux systems
3.1. Prerequisites
3.1.1. Installing pre-compiled packages
3.1.2. Compiling Ipopt
3.1.3. Installing JModelica.org with WORHP (optional)
3.2. Compiling
3.3. Testing JModelica.org
3. Getting started
1. The JModelica.org Python packages
2. Starting a Python session
2.1. Windows
2.2. Linux
3. Run an example
4. Check your installation
5. Redefining the JModelica.org environment
5.1. Example redefining IPOPT_HOME
6. The JModelica.org user forum
4. Working with Models
1. Introduction to models
1.1. The different model objects in JModelica.org
2. Compilation
2.1. Simple FMU-ME compilation example
2.2. Simple FMU-CS compilation example
2.3. Simple JMU compilation example
2.4. Compiling from libraries
2.5. Compiler settings
2.5.1. compile_fmu parameters
2.5.2. Compiler options
2.6. Compile in separate process
2.7. Compilation in more detail
2.7.1. Create a compiler
2.7.2. Source tree generation and flattening
2.7.3. Code generation
3. Loading models
3.1. The FMU
3.2. The JMU
3.3. Loading an FMU
3.4. Loading a JMU
3.5. Transferring an OptimizationProblem
4. Changing model parameters
4.1. Setting and getting parameters
5. Debugging models
5.1. Compiler logging
5.2. Runtime logging
5.2.1. Setting log level
5.2.2. Interpreting logs from JModelica.org
5.3. Getting HTML diagnostics
5. Simulation of FMUs
1. Introduction
2. A first example
3. Simulation of Models
3.1. Convenience method, load_fmu
3.2. Arguments
3.2.1. Input
3.2.2. Options for FMUModelME1 and FMUModelME2
3.2.3. Options for FMUModelCS1 and FMUModelCS2
3.3. Return argument
4. Examples
4.1. Simulation of a high-index model
4.2. Simulation and parameter sweeps
4.3. Simulation of an Engine model with inputs
4.4. Simulation using the native FMI interface
4.4.1. Implementation
4.5. Simulation of Co-Simulation FMUs
6. Optimization
1. Introduction
2. A first example
3. Solving optimization problems
4. Scaling
5. Dynamic optimization of DAEs using direct collocation with CasADi
5.1. Algorithm overview
5.2. Examples
5.2.1. Optimal control
5.2.2. Minimum time problems
5.2.3. Optimization under delay constraints
6. Derivative-Free Model Calibration of FMUs
7. Graphical User Interface for Visualization of Results
1. Plot GUI
1.1. Introduction
1.2. Edit Options
1.3. View Options
1.4. Example
8. Optimica
1. A new specialized class: optimization
2. Attributes for the built in class Real
3. A Function for accessing instant values of a variable
4. Class attributes
5. Constraints
9. Abstract syntax tree access
1. Tutorial on Abstract Syntax Trees (ASTs)
1.1. About Abstract Syntax Trees
1.2. Load the Modelica standard library
1.3. Count the number of classes in the Modelica standard library
1.4. Dump the instance AST
1.5. Flattening of the filter model
10. Limitations
A. Release notes
1. Release notes for JModelica.org version 1.15
1.1. Highlights
1.2. Compiler
1.2.1. Compliance
1.2.2. Support for over-constrained initialization systems
1.2.3. FMU 2.0 export
1.2.4. Improved numerical algorithms in FMU runtime
1.2.5. CasADi 2.0 support in Optimization
1.3. Simulation
2. Release notes for JModelica.org version 1.14
2.1. Highlights
2.2. Compiler
2.2.1. Compliance
2.2.2. New compiler API
2.2.3. FMI 2.0 RC2 export
2.3. Simulation
2.4. Optimization
3. Release notes for JModelica.org version 1.13
3.1. Highlights
3.2. Compilers
3.2.1. FMI 2.0 RC1 export
3.2.2. Compliance
3.3. Simulation
3.3.1. In-lined switches
3.4. Optimization
3.4.1. New CasADi tool chain
4. Release notes for JModelica.org version 1.12
4.1. Highlights
4.2. Compilers
4.3. Simulation
4.4. Contributors
4.4.1. Previous contributors
5. Release notes for JModelica.org version 1.11
5.1. Highlights
5.2. Compilers
5.3. Simulation
5.3.1. Runtime logging
5.3.2. Support for ModelicaError and assert
5.4. Contributors
5.4.1. Previous contributors
6. Release notes for JModelica.org version 1.10
6.1. Highlights
6.2. Compilers
6.2.1. Export of FMUs for Co-Simulation
6.3. Python
6.3.1. Improved result data access
6.3.2. Improved error handling
6.3.3. Parsing of FMU log files
6.4. Simulation
6.4.1. Support for FMU version 2.0b4
6.4.2. Result filter
6.4.3. Improved solver support
6.5. Optimization
6.5.1. Improved variable scaling
6.5.2. Improved handling of measurement data
6.6. Contributors
6.6.1. Previous contributors
7. Release notes for JModelica.org version 1.9.1
8. Release notes for JModelica.org version 1.9
8.1. Highlights
8.2. Compilers
8.2.1. Improved Modelica compliance
8.2.2. Support for MSL CombiTables
8.2.3. Support for hand guided tearing
8.2.4. Improved function inlining
8.2.5. Memory and execution time improvements in the compiler
8.3. Python
8.3.1. Compile in separate process
8.4. Simulation
8.4.1. Simulation of co-simulation FMUs
8.5. Optimization
8.5.1. Improvements to CasADi-based collocation algorithm
8.6. Contributors
8.6.1. Previous contributors
9. Release notes for JModelica.org version 1.8.1
10. Release notes for JModelica.org version 1.8
10.1. Highlights
10.2. Compilers
10.2.1. Improved Modelica compliance
10.2.2. Function inlining
10.2.3. New state selection algorithm
10.3. Python
10.3.1. Simplified compiling with libraries
10.4. Optimization
10.4.1. Improvements to CasADi-based collocation algorithm
10.5. Contributors
10.5.1. Previous contributors
11. Release notes for JModelica.org version 1.7
11.1. Highlights
11.2. Compilers
11.2.1. Support for mixed systems of equations
11.2.2. Support for tearing
11.2.3. Improved Modelica compliance
11.2.4. Function inlining
11.3. Python
11.3.1. New package structure
11.3.2. Support for shared libraries in FMUs
11.4. Simulation
11.4.1. Simulation of hybrid systems
11.5. Optimization
11.5.1. A novel CasADi-based collocation algorithm
11.6. Contributors
11.6.1. Previous contributors
12. Release notes for JModelica.org version 1.6
12.1. Highlights
12.2. Compilers
12.2.1. Index reduction
12.2.2. Modelica compliance
12.3. Python
12.3.1. Graphical user interface for visualization of simulation and optimization results
12.3.2. Simulation with function inputs
12.3.3. Compilation of XML models
12.3.4. Python version upgrade
12.4. Optimization
12.4.1. Derivative- free optimization of FMUs
12.4.2. Pseudo spectral methods for dynamic optimization
12.5. Eclipse Modelica plugin
12.6. Contributors
12.6.1. Previous contributors
13. Release notes for JModelica.org version 1.5
13.1. Highlights
13.2. Compilers
13.2.1. When clauses
13.2.2. Equation sorting
13.2.3. Connections
13.2.4. Eclipse IDE
13.2.5. Miscellaneous
13.3. Simulation
13.3.1. FMU export
13.3.2. Simulation of ODEs
13.3.3. Simulation of hybrid and sampled systems
13.4. Initialization of DAEs
13.5. Optimization
13.6. Contributors
13.6.1. Previous contributors
14. Release notes for JModelica.org version 1.4
14.1. Highlights
14.2. Compilers
14.2.1. Enumerations
14.2.2. Miscellaneous
14.2.3. Improved reporting of structural singularities
14.2.4. Automatic addition of initial equations
14.3. Python interface
14.3.1. Models
14.3.2. Compiling
14.3.3. initialize, simulate and optimize
14.3.4. Result object
14.4. Simulation
14.4.1. Input trajectories
14.4.2. Sensitivity calculations
14.4.3. Write scaled simulation result to file
14.5. Contributors
14.5.1. Previous contributors
15. Release notes for JModelica.org version 1.3
15.1. Highlights
15.2. Compilers
15.2.1. The Modelica compiler
15.2.2. The Optimica compiler
15.3. JModelica.org Model Interface (JMI)
15.3.1. The collocation optimization algorithm
15.4. Assimulo
15.5. FMI compliance
15.6. XML model export
15.6.1. noEvent operator
15.6.2. static attribute
15.7. Python integration
15.7.1. High-level functions
15.7.2. File I/O
15.8. Contributors
15.8.1. Previous contributors
16. Release notes for JModelica.org version 1.2
16.1. Highlights
16.2. Compilers
16.2.1. The Modelica compiler
16.2.2. The Optimica Compiler
16.3. The JModelica.org Model Interface (JMI)
16.3.1. General
16.4. The collocation optimization algorithm
16.4.1. Piecewise constant control signals
16.4.2. Free initial conditions allowed
16.4.3. Dens output of optimization result
16.5. New simulation package: Assimulo
16.6. FMI compliance
16.7. XML model export
16.8. Python integration
16.8.1. New high-level functions for optimization and simulation
16.9. Contributors
16.9.1. Previous contributors
B. Initialization and simulation of JMUs (Deprecated in JModelica.org 1.15)
1. Introduction
2. Initialization of JMUs
2.1. Solving DAE initialization problems
2.2. How JModelica.org creates the initialization system of equations
2.3. Initialization algorithms
2.3.1. Initialization using IPOPT
2.3.2. Initialization using KInitSolveAlg
3. Simulation of JMUs
3.1. The simulate function
3.1.1. Input
3.1.2. Options for JMUModel
3.1.3. Return argument
3.2. Examples
3.2.1. Simulation with inputs
3.2.2. Simulation of a discontinuous system
3.2.3. Simulation with sensitivities
C. Dynamic optimization of DAEs using direct collocation with JMUs (Deprecated in JModelica.org 1.15)
1. Dynamic optimization of DAEs using direct collocation with JMUs
1.1. Examples
1.1.1. Optimal control
1.1.2. Minimum time problems
1.1.3. Parameter optimization
Bibliography

List of Figures

1.1. JModelica.org platform architecture.
2.1. Selecting Python packages in the Choose components window.
5.1. Simulation result of the Van der Pol oscillator.
5.2. Modelica.Mechanics.Rotational.First connection diagram
5.3. Simulation result for Modelica.Mechanics.Rotational.Examples.First
5.4. Simulation result-phase plane
5.5. Overview of the Engine model
5.6. Resulting trajectories for the engine model.
5.7. Simulation result
5.8. Simulation result
6.1. Optimal profiles for the VDP oscillator
6.2. Optimal profiles for the CSTR problem.
6.3. Optimal control profiles and simulated trajectories corresponding to the optimal control input.
6.4. Minimum time profiles for the Van der Pol Oscillator.
6.5. Optimization result for delayed feedback example.
6.6. The Furuta pendulum.
6.7. Measurements of Measurements of and for the Furuta pendulum. and Measurements of and for the Furuta pendulum. for the Furuta pendulum.
6.8. Measurements and model simulation result for Measurements and model simulation result for and when using nominal parameter values in the Furuta pendulum model. and Measurements and model simulation result for and when using nominal parameter values in the Furuta pendulum model. when using nominal parameter values in the Furuta pendulum model.
6.9. Measurements and model simulation results for Measurements and model simulation results for and with nominal and optimal parameters in the model of the Furuta pendulum. and Measurements and model simulation results for and with nominal and optimal parameters in the model of the Furuta pendulum. with nominal and optimal parameters in the model of the Furuta pendulum.
7.1. Overview of JModelica.org Plot GUI
7.2. A result file has been loaded.
7.3. Plotting a trajectory.
7.4. Figure Options.
7.5. Figure Axis and Labels Options.
7.6. Figure Lines and Legends options.
7.7. An additional plot has been added.
7.8. Moving Plot Figure.
7.9. GUI after moving the plot window.
7.10. Complex Figure Layout.
7.11. Figure View Options.
7.12. Multiple figure example.
8.1. Optimization result
B.1. A schematic picture of the quadruple tank process.
B.2. Tank levels
B.3. Input trajectories
B.4. Electric Circuit
B.5. Simulation result
B.6. Sensitivity results.
C.1. Optimal profiles for the CSTR problem.
C.2. Optimal control profiles and simulated trajectories corresponding to the optimal control input.
C.3. Minimum time profiles for the Van der Pol Oscillator.
C.4. A schematic picture of the quadruple tank process.
C.5. Measured state profiles.
C.6. Control inputs used in the identification experiment.
C.7. Simulation result for the nominal model.
C.8. State profiles corresponding to estimated values of a1 and a2.
C.9. State profiles corresponding to estimated values of a1, a2, a3 and a4.

List of Tables

2.1. Package versions for Ubuntu
4.1. Compiler options
5.1. General options for AssimuloFMIAlg.
5.2. Selection of solver arguments for CVode
5.3. General options for FMICSAlg.
5.4. Result Object
6.1. Options for the CasADi- and collocation-based optimization algorithm
B.1. Options for the collocation-based optimization algorithm
B.2. Options for KInitSolveAlg
B.3. Options for KINSOL contained in the KINSOL_options dictionary
B.4. Values allowed in the constraints array
B.5. Verbosity levels in KINSOL
B.6. General options for AssimuloAlg.
B.7. Selection of solver arguments for CVode
B.8. Selection of solver arguments for IDA
B.9. Result Object
C.1. Options for the JMU and collocation-based optimization algorithm
C.2. Parameters for the quadruple tank process.