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Highlights from
Speeding Up Optimization Problems with Parallel Computing

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Speeding Up Optimization Problems with Parallel Computing

by

Stuart Kozola (view profile)

 

Files from the webinar: Speeding up optimization problems with parallel computing

Editor's Notes:

This file was selected as MATLAB Central Pick of the Week

flutterLimitFunction(X,model)
function failed = flutterLimitFunction(X,model)
% Calcualte Flutter Limit Function

% Copyright 2010 The MathWorks, Inc.
%% Scale X's
% Good practice to scale variables of different magnitudes when using
% optimization, need to scale back to model units.
X(1) = X(1)/10;    % Mach Scaling
X(2) = X(2)*10000; % Altitude Scaling

%% Run Simulink Model
Mach = X(1);
Altitude = X(2);
setup
s = sim(model,'SrcWorkspace','current');
sigsOut = get(s,'sigsOut');

%% Extract Failure Measure
try
    failed = sigsOut.isStable.Data(end);
catch
    disp('Stopped here because of error')
end

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