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Merge pull request #27 from tinrabuzin/setup_example
Running SecondOrder example during setup
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| %% ==========Moving to the example folder========== | ||
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| [str,~,~] = fileparts(mfilename('fullpath')); | ||
| oldFolder=cd(str); | ||
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| %% ==========Reference data settings========== | ||
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| % Create a RaPIdObject (optional but recommended - will work with just a structure) | ||
| RaPIdObject=RaPIdClass(); | ||
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| %Output data | ||
| RaPIdObject.experimentData.pathToReferenceData = 'measuredDataO.mat'; %Data file name | ||
| RaPIdObject.experimentData.expressionReferenceTime = 'time'; %Time variable name | ||
| RaPIdObject.experimentData.expressionReferenceData = 'signal'; %Data variable name | ||
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| %Input data | ||
| RaPIdObject.experimentData.pathToInData = ''; | ||
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| %% ==========Experiment settings========== | ||
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| %General settings | ||
| RaPIdObject.experimentSettings.tf = 50; %Simulation length | ||
| RaPIdObject.experimentSettings.ts = 0.01; %Sampling time | ||
| RaPIdObject.experimentSettings.t_fitness_start = 4; %Start calculating fintess function after t_fintess_start | ||
| RaPIdObject.experimentSettings.timeOut = 2; %Seconds before simulation timeout | ||
| RaPIdObject.experimentSettings.integrationMethod = 'ode45'; %Solver selection | ||
| RaPIdObject.experimentSettings.solverMode = 'Simulink'; | ||
| RaPIdObject.experimentSettings.optimizationAlgorithm = 'pso'; %Selection of optimization algorithm | ||
| RaPIdObject.experimentSettings.maxIterations = 100; %Maximum number of estimation iterations | ||
| RaPIdObject.experimentSettings.verbose = 1; %Can trigger more data for debugging | ||
| RaPIdObject.experimentSettings.saveHist = 0; %Don't save history | ||
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| %Model related settings | ||
| RaPIdObject.experimentSettings.pathToSimulinkModel = 'variable_rafael.mdl'; %Simulink model file name | ||
| RaPIdObject.experimentSettings.pathToFMUModel = 'Rafael_0original_0estimated.fmu'; %FMU file name | ||
| RaPIdObject.experimentSettings.modelName = 'variable_rafael'; %Simulink model name | ||
| RaPIdObject.experimentSettings.blockName = 'variable_rafael/Rafael_original_estimated'; %FMU name | ||
| RaPIdObject.experimentSettings.scopeName = 'simout'; %Result sink name | ||
| RaPIdObject.experimentSettings.displayMode = 'Show'; | ||
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| %Estimation parameter settings | ||
| RaPIdObject.experimentSettings.p_0 = [0.3, 4.1, 1.7, 1.1]; %Initial parameter guess | ||
| RaPIdObject.experimentSettings.p_min = [0.1, 3.9, 1.5, 1.1]; %Minimum values of parameters | ||
| RaPIdObject.experimentSettings.p_max = [1, 4.2, 1.7, 1.5]; %Maximum values of parameters | ||
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| %Fitness function settings | ||
| RaPIdObject.experimentSettings.cost_type = 1; %Fitness function selection | ||
| RaPIdObject.experimentSettings.objective_weights = 1; %Weights of the output signals for fitness function | ||
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| %% ==========Optimization Algorithm settings========== | ||
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| switch RaPIdObject.experimentSettings.optimizationAlgorithm | ||
| case 'pso' | ||
| RaPIdObject.psoSettings.w = 0.25; %Particle inertia weight | ||
| RaPIdObject.psoSettings.self_coeff = 0.25; %Self recognition coefficient | ||
| RaPIdObject.psoSettings.social_coeff = 0.25; %Social coefficient | ||
| RaPIdObject.psoSettings.limit = 0.25; %Iteration limit | ||
| RaPIdObject.psoSettings.nRandMin = 8; %Minimum number of random particles | ||
| RaPIdObject.psoSettings.nb_particles = 8; %Number of particles | ||
| RaPIdObject.psoSettings.fitnessStopRatio = 1e-5; %Fitness stop ratio | ||
| RaPIdObject.psoSettings.kick_multiplier = 0.002; %Kick multiplier | ||
| RaPIdObject.psoSettings.method = 'PSO'; | ||
| end | ||
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| %% ==========FMU parameters, inputs and outputs========== | ||
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| RaPIdObject.parameterNames = {'transferFunction.b[1]','transferFunction.a[1]','transferFunction.a[2]','transferFunction.a[3]'}; | ||
| RaPIdObject.fmuInputNames = {}; | ||
| RaPIdObject.fmuOutputNames = {'y1'}; %Output variable names | ||
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| %% ==========Running the computation========== | ||
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| %Opening simulink model | ||
| open_system(RaPIdObject.experimentSettings.pathToSimulinkModel); %Opening the simulink model | ||
| open_system(strcat(RaPIdObject.experimentSettings.modelName,'/Scope')); %Opening the scope in the model to observe estimation process | ||
| pause(1); %Waiting one second for scope to initialize | ||
| %% | ||
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| %Starting the estimation process | ||
| [sol, hist] = rapid(RaPIdObject); | ||
| sprintf('Vector of estimated parameters is: %s',mat2str(sol,3)) | ||
| %Restoring workspace | ||
| cd(oldFolder); | ||
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| %% <Rapid Parameter Identification is a toolbox for automated parameter identification> | ||
| % | ||
| % Copyright 2015 Luigi Vanfretti, Achour Amazouz, Maxime Baudette, | ||
| % Tetiana Bogodorova, Jan Lavenius, Tin Rabuzin, Giuseppe Laera, | ||
| % Francisco Gomez-Lopez | ||
| % | ||
| % The authors can be contacted by email: luigiv at kth dot se | ||
| % | ||
| % This file is part of Rapid Parameter Identification ("RaPId") . | ||
| % | ||
| % RaPId is free software: you can redistribute it and/or modify | ||
| % it under the terms of the GNU Lesser General Public License as published by | ||
| % the Free Software Foundation, either version 3 of the License, or | ||
| % (at your option) any later version. | ||
| % | ||
| % RaPId is distributed in the hope that it will be useful, | ||
| % but WITHOUT ANY WARRANTY; without even the implied warranty of | ||
| % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | ||
| % GNU Lesser General Public License for more details. | ||
| % | ||
| % You should have received a copy of the GNU Lesser General Public License | ||
| % along with RaPId. If not, see <http://www.gnu.org/licenses/>. | ||
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| classdef RaPIdClass <handle | ||
| %RAPIDCLASS defines a handle object to store and send settings and data in RaPId | ||
| % without too much overhead | ||
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| properties | ||
| psoSettings | ||
| gaSettings | ||
| combiSettings | ||
| naiveSettings | ||
| knitroSettings | ||
| nmSettings | ||
| cgSettings | ||
| psoExtSettings | ||
| gaExtSettings | ||
| fminconSettings | ||
| pfSettings | ||
| experimentSettings | ||
| experimentData | ||
| resultData | ||
| fmuOutputNames | ||
| parameterNames | ||
| fmuInputNames | ||
| version; %decimals of sqrt(2) | ||
| end | ||
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| methods (Static) | ||
| function obj = loadobj(s)% Implements self-updating loading features to ensure backwards | ||
| % compatibility with old objects | ||
| try | ||
| if ~isprop(s, 'version') || isempty(s.version) % if no version -> assign version=1 | ||
| s.version=double(~isempty(isprop(s, 'version'))); % 0 if really old, else 1 - old | ||
| obj = RaPIdClass(s); % update object | ||
| elseif s.version <1.41 % check if latest ver | ||
| obj = RaPIdClass(s); % update object | ||
| else | ||
| obj=s; % everything is up to date | ||
| end | ||
| catch err | ||
| disp(err) | ||
| disp(struct2table(err.stack)) | ||
| end | ||
| end | ||
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| end | ||
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| methods | ||
| function obj = RaPIdClass(varargin) %Constructor | ||
| if nargin == 0 %Create a new object of the latest version | ||
| try | ||
| obj=initRapidObj(obj); | ||
| catch | ||
| %NOP, will still give a an object | ||
| end | ||
| elseif isa(varargin{1},'RaPIdClass') && varargin{1}.version==1.41 | ||
| %NOP, up to date | ||
| else % Old version, try to update | ||
| obj=RaPIdClass(); % New object | ||
| obj=obj.updateRapidObj(varargin{1}); % update old object | ||
| end | ||
| end | ||
| function obj = saveobj(obj) | ||
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| end | ||
| end | ||
| end |
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| function obj = initRapidObj(obj) | ||
| % INITRAPIDOBJ this function is meant to create a default rapidobject | ||
| % Detailed explanation goes here | ||
| obj.experimentSettings=struct('tf',1,'ts',0.1,'p_min',[],'p_max',[],'p_0',[],... | ||
| 'cost_type',1,'objective_weights',1,'t_fitness_start',0,... | ||
| 'integrationMethod','ode45','maxIterations',100,'solverMode','Simulink',... | ||
| 'pathToSimulinkModel','','modelName','','blockName','','scopeName','simout',... | ||
| 'verbose',1,'displayMode','hide','saveHist',0,'timeOut',2,... | ||
| 'pathToFmuModel','','outputPostProcessing','','optimizationAlgorithm','pso',... | ||
| 'pathToFMUModel',''); | ||
| obj.experimentData = struct('pathToInData','','expressionInData','',... | ||
| 'expressionInDataTime','','referenceOutdata',[],'referenceTime',[],... | ||
| 'pathToReferenceData','','expressionReferenceTime','','expressionReferenceData',''); | ||
| obj.psoSettings=struct('w',0.25,'self_coeff',0.25,'social_coeff',0.25,... | ||
| 'limit',0.2500,'nRandMin',8,'nb_particles',8,'fitnessStopRatio',1e-5,... | ||
| 'kick_multiplier',0.002,'w_min', 0.01, 'w_max',1,'method','PSO'); | ||
| obj.gaSettings=struct('nbCromosomes',40,'nbCroossOver1',10,'nbCroossOver2',10,... | ||
| 'nbMutations',10,'nbReproduction',10,'limit',10,'fitnessStopRatio',1e-5,... | ||
| 'headSize1',5,'headSize2',5,'headSize3',3,'nbReinjection',5,'nRandMin',10, ... | ||
| 'p0s', [],'storeData',0); | ||
| obj.combiSettings=struct('firstMethod','pso','psoExtOptions','nm','secondMetod','nm'); | ||
| obj.naiveSettings=struct('tolerance1',1e-4,'tolerance2',1e-7,'iterations',1,'iterations2',1,'iterations3',1); | ||
| obj.knitroSettings=struct('path2Knitro','','knOptionsFile','', ... | ||
| 'knOptions','optimset(''Algorithm'',''active-set'',''TolFun'',1e-6,''TolX'',1e-6);'); | ||
| obj.nmSettings='optimset(''fminsearch'')'; | ||
| obj.cgSettings='optimset(optimset(''fminunc''),''FinDiffType'',''central'',''TolX'',1e-6,''LargeScale'',''off'')'; | ||
| obj.psoExtSettings='psoptimset'; | ||
| obj.gaExtSettings='gaoptimset'; | ||
| obj.fminconSettings='optimset(''FinDiffRelStep'',0.1)'; | ||
| obj.pfSettings=struct('nb_particles', 100,'prune_threshold', 0.1,'kernel_sigma',1); | ||
| obj.resultData=[]; | ||
| obj.fmuOutputNames={''}; | ||
| obj.parameterNames={''}; | ||
| obj.fmuInputNames={''}; | ||
| obj.version=1.41; | ||
| end | ||
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