Outline: Outline: -Motivations of GAPI Lib -Why GAs? -Structure of - - PDF document

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An An Approach Approach to to the the Calibration Calibration of

• f

Modelica Modelica Models Models

M.A M.A. Rubio, A. Urquia, S. Dormido . Rubio, A. Urquia, S. Dormido Departamento de Inform Departamento de Informá ática y Autom tica y Automá ática tica EOOLT 2007 EOOLT 2007

Outline: Outline:

• Motivations of GAPILib
• Why GAs?
• Structure of GAs
• GAPILib architecture
• New capabilities of GAPILib
• Some results
• Conclusions
• Future work

An Approach to the Calibration of Modelica Models

EOOLT 2007 EOOLT 2007

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An Approach to the Calibration of Modelica Models

• A model has usually some parameters with unknown values.
• The validation process requires to estimate this group of parameters.
• GAPILib is a tool to fit the parameters from experimental data.

Fitness of parameters Optimization

• To fit some parameters of a model to improve the behavior of the real plant.
• Motivations

Motivations of

• f GAPI

GAPILib Lib

EOOLT 2007 EOOLT 2007 A free-availiable optimization tool for Modelica models

• Robustness and simplicity: without needing to modify the

model.

• Finding solutions in high-dimensional search spaces.
• The search range of the parameters can be changed during

the algorithm run.

• Parallel implementations of GAs, intended to reduce the

computation time.

• Why

Why GAs? GAs?

An Approach to the Calibration of Modelica Models

EOOLT 2007 EOOLT 2007

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• Structure

Structure of

• f GAs

GAs

The GA starts with an initial population, which is randomly selected from the search space. Each individual of the population is formed by a group of chromosomes, which represents a solution to the problem.

An Approach to the Calibration of Modelica Models

EOOLT 2007 EOOLT 2007

This population is evaluated by using a cost function. This function is used to calculate the validity of the population members, which are

• rdered according to this criterion.

An Approach to the Calibration of Modelica Models

• Structure

Structure of

• f GAs (II)

GAs (II)

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The most valid members are selected for the crossover process, which generates a new population.

An Approach to the Calibration of Modelica Models

• Structure

Structure of

• f GAs (III)

GAs (III)

EOOLT 2007 EOOLT 2007

The GA supported by GAPILib includes several processes intended to improve the algorithm performance: + Elitism ensures that the most valid individuals pass on to the next generation. + Mutation introduces random changes on the

• individuals. The purpose of mutation is to allow

the algorithm to avoid local minima.

An Approach to the Calibration of Modelica Models

• Structure

Structure of

• f GAs (IV)

GAs (IV)

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The stop condition is not satisfied, the algorithm goes on. The new generation completes a new cycle of the algorithm.

An Approach to the Calibration of Modelica Models

• Structure

Structure of

• f GAs (V)

GAs (V)

EOOLT 2007 EOOLT 2007

An Approach to the Calibration of Modelica Models

• GAPI

GAPILib Lib architecture architecture

EOOLT 2007 EOOLT 2007

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An Approach to the Calibration of Modelica Models

EOOLT 2007 EOOLT 2007

• GAPI

GAPILib Lib architecture architecture (II) (II)

An Approach to the Calibration of Modelica Models

• New

New capabilities capabilities of

• f GAPI

GAPILib Lib

EOOLT 2007 EOOLT 2007

Runtime monitoring of the algorithm convergence Interactivity of the GA parameters

• Range of parameters (Auto-Interactivity-Fixed)
• Elitism factor
• Mutation factor
• Cross point

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An Approach to the Calibration of Modelica Models

EOOLT 2007 EOOLT 2007

• New

New capabilities capabilities of

• f GAPI

GAPILib (II) Lib (II)

Parameter sensitivity Parallel computing of the GA

An Approach to the Calibration of Modelica Models

• Some

Some results results

EOOLT 2007 EOOLT 2007

Polarization curves of PEMFCs

NParameters =7 NCycle = 5000 NPopulation =100 Fmut =0.25 NParents =70 NElitism =1

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An Approach to the Calibration of Modelica Models

EOOLT 2007 EOOLT 2007

• Some

Some results results (II) (II)

NParameters =4 NCycle =200 NPopulation =150 Fmut =0.25 NParents =100 NElitism =1

Fuel cell voltage in response to step changes in the load

An Approach to the Calibration of Modelica Models

EOOLT 2007 EOOLT 2007

• Some

Some results results (III) (III)

NParameters =5 NCycle =700 NPopulation =70 Fmut =0.15 NParents =50 NElitism =1

Effect of water on the fuel cell voltage with constant resistance load

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An Approach to the Calibration of Modelica Models

• Conclusions

Conclusions

EOOLT 2007 EOOLT 2007

• GAPILib is an effective tool for parameter identification

in Modelica models using GA.

• It is completely written in the Modelica language, which

facilitates its use, modification and extension.

• GAPILib is a free library.

An Approach to the Calibration of Modelica Models

• Future

Future Work Work

EOOLT 2007 EOOLT 2007

• Implementation of parallel structure.
• Theoretical study of the parameters´ sensibility.
• Improvement of its capability for optimization.

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Departamento de Inform Departamento de Informá ática y Autom tica y Automá ática tica

THE END THE END

E E-

• mail:

mail: marubio@dia.uned.es marubio@dia.uned.es GAPI GAPILib Web: Lib Web: www.euclides.dia.uned.es www.euclides.dia.uned.es

EOOLT 2007 EOOLT 2007