what is wrong on my codes ? I can not get my result any one help?

% This script is used to run a genetic algorithm to optimize the parameters of a nonlinear damping system model

clear % Clear the workspace
clc   % Clear the command window

% Define the parameters for the system
A = eye(5); % Define a 5x5 identity matrix

% Set the bounds for the optimization variables
b = [65; 290; 200; 200; 200; 200];
UB = [65; 290; 200; 200; 200; 200];
lb = [48; 215; 30; 50; 20; 20];
LB = [48; 215; 30; 50; 20; 20];

% Run the genetic algorithm to optimize the parameters using the TMD_nonlineardamploop function
[x, fval, exitflag] = ga(@TMD_nonlineardamploop, 6, A, b, [], [], LB, UB, [], [1, 2, 3, 4, 5, 6]);

Error using globaloptim.internal.preProcessLinearConstr
The number of rows in A must be the same as the length of b.

Error in gacommon (line 150)
globaloptim.internal.preProcessLinearConstr(Iterate.x,Aineq,bineq, ...

Error in ga (line 377)
NonconFcn,options,Iterate,type] = gacommon(nvars,fun,Aineq,bineq,Aeq,beq,lb,ub, ...

function y = TMD_nonlineardamploop(x)
% This function calculates the response of a nonlinear damping system model
% Inputs:
% - x: Vector of optimization variables containing parameters for the system
% Outputs:
% - y: Maximum displacement of the system

if ~isvector(x)
    error('Input must be a vector');
end

% Extract the optimization variables
Kxt = x(1);
Kyt = x(2);
Kzt = x(3);
Kisayx = x(4) / 1000;
Kisayy = x(5) / 1000;
Kisayz = x(6) / 1000;

% Define system parameters
Ly = x(5) / 100;
m = 30;
Kx = 1320; Ky = 1320 * 90.0;
wx = (Kx / m)^0.5;
mt = 1.5 * 2 / 2 / 2;
Lx = 1;
Cx = 2 * 0.025 * 4 * (Kx / m)^0.5 * m;
Cy = 2 * 0.025 * 4 * (Ky / m)^0.5 * m;

% Define the mass, stiffness, and damping matrices
M = [m 0 0 0; 0 m 0 0; 0 0 mt 0; 0 0 0 mt; 0 0 0 mt];
K = [Kx + Kxt 0 -Kxt 0; 0 Ky + Kyt 0 -Kyt; 0 Kz + Kzt 0 -Kzt; -Kxt 0 Kxt 0; 0 -Kyt 0 Kyt; 0 -Kzt 0 Kzt];
C = [Cx + Cxt 0 -Cxt 0; 0 Cy + Cyt 0 -Cyt; Cz + Czt 0 0 -Czt; -Cyt; -Cxt 0 Cxt 0; 0 -Cyt 0 Cyt; 0 -Czt 0 Czt];

...
    
% Run the nonlinear simulation and store the results
non_linansw = [C_MMM1', MMM(:,1), MMM(:,2), MMM(:,3)];

% Return the maximum displacement of the system
y = max(max([non_linansw(:,2), non_linansw(:,3)]));
end

[Torsten]

Where is ... ?

Answer 1

[Walter Roberson]

You need

A = eye(6);

However, A*x <= b with A = eye(6) is equivalent to x <= b which is the same thing expressed by UB, so there is no point in using that A b combination. You might as well use A = []; b = [];

[Doha Ali]

hi, how are you? still I have error and I dont get any result can you run for me and give me the result ?

[Walter Roberson]

You do not define Kz

% This script is used to run a genetic algorithm to optimize the parameters of a nonlinear damping system model

clear % Clear the workspace
clc   % Clear the command window

% Define the parameters for the system
A = eye(6); % Define a 5x5 identity matrix

% Set the bounds for the optimization variables
b = [65; 290; 200; 200; 200; 200];
UB = [65; 290; 200; 200; 200; 200];
lb = [48; 215; 30; 50; 20; 20];
LB = [48; 215; 30; 50; 20; 20];

% Run the genetic algorithm to optimize the parameters using the TMD_nonlineardamploop function
[x, fval, exitflag] = ga(@TMD_nonlineardamploop, 6, A, b, [], [], LB, UB, [], [1, 2, 3, 4, 5, 6]);

Unrecognized function or variable 'Kz'.

Error in solution>TMD_nonlineardamploop (line 49)
K = [Kx + Kxt 0 -Kxt 0; 0 Ky + Kyt 0 -Kyt; 0 Kz + Kzt 0 -Kzt; -Kxt 0 Kxt 0; 0 -Kyt 0 Kyt; 0 -Kzt 0 Kzt];

Error in createAnonymousFcn>@(x)fcn(x,FcnArgs{:}) (line 11)
fcn_handle = @(x) fcn(x,FcnArgs{:});

Error in fcnvectorizer (line 19)
y(i,:) = feval(fun,(pop(i,:)));

Error in gaminlppenaltyfcn

Error in gapenalty

Error in makeState (line 76)
Score = FitnessFcn(state.Population(initScoreProvided+1:end,:));

Error in galincon (line 24)
state = makeState(GenomeLength,FitnessFcn,Iterate,output.problemtype,options);

Error in gapenalty

Error in ga (line 412)
[x,fval,exitFlag,output,population,scores] = gapenalty(FitnessFcn,nvars,...

Caused by:
Failure in user-supplied fitness function evaluation. GA cannot continue.
Failure in initial user-supplied fitness function evaluation. GA cannot continue.

function y = TMD_nonlineardamploop(x)
% This function calculates the response of a nonlinear damping system model
% Inputs:
% - x: Vector of optimization variables containing parameters for the system
% Outputs:
% - y: Maximum displacement of the system

if ~isvector(x)
    error('Input must be a vector');
end

% Extract the optimization variables
Kxt = x(1);
Kyt = x(2);
Kzt = x(3);
Kisayx = x(4) / 1000;
Kisayy = x(5) / 1000;
Kisayz = x(6) / 1000;

% Define system parameters
Ly = x(5) / 100;
m = 30;
Kx = 1320; Ky = 1320 * 90.0;
wx = (Kx / m)^0.5;
mt = 1.5 * 2 / 2 / 2;
Lx = 1;
Cx = 2 * 0.025 * 4 * (Kx / m)^0.5 * m;
Cy = 2 * 0.025 * 4 * (Ky / m)^0.5 * m;

% Define the mass, stiffness, and damping matrices
M = [m 0 0 0; 0 m 0 0; 0 0 mt 0; 0 0 0 mt; 0 0 0 mt];
K = [Kx + Kxt 0 -Kxt 0; 0 Ky + Kyt 0 -Kyt; 0 Kz + Kzt 0 -Kzt; -Kxt 0 Kxt 0; 0 -Kyt 0 Kyt; 0 -Kzt 0 Kzt];
C = [Cx + Cxt 0 -Cxt 0; 0 Cy + Cyt 0 -Cyt; Cz + Czt 0 0 -Czt; -Cyt; -Cxt 0 Cxt 0; 0 -Cyt 0 Cyt; 0 -Czt 0 Czt];

...
    
% Run the nonlinear simulation and store the results
non_linansw = [C_MMM1', MMM(:,1), MMM(:,2), MMM(:,3)];

% Return the maximum displacement of the system
y = max(max([non_linansw(:,2), non_linansw(:,3)]));
end

[Doha Ali]

ok,can you use this ? I define kz

% This script is used to run a genetic algorithm to optimize the parameters of a nonlinear damping system model

clear % Clear the workspace
clc   % Clear the command window

% Define the parameters for the system
A = eye(6); % Define a 5x5 identity matrix

% Set the bounds for the optimization variables
b = [65; 290; 200; 200; 200; 200];
UB = [65; 290; 200; 200; 200; 200];
lb = [48; 215; 30; 50; 20; 20];
LB = [48; 215; 30; 50; 20; 20];

% Run the genetic algorithm to optimize the parameters using the TMD_nonlineardamploop function
[x, fval, exitflag] = ga(@TMD_nonlineardamploop, 6, A, b, [], [], LB, UB, [], [1, 2, 3, 4, 5, 6]);

function y = TMD_nonlineardamploop(x)
% This function calculates the response of a nonlinear damping system model
% Inputs:
% - x: Vector of optimization variables containing parameters for the system
% Outputs:
% - y: Maximum displacement of the system

if ~isvector(x)
    error('Input must be a vector');
end

% Extract the optimization variables
Kxt = x(1);
Kyt = x(2);
Kzt = x(3);
Kisayx = x(4) / 1000;
Kisayy = x(5) / 1000;
Kisayz = x(6) / 1000;

% Define system parameters
Ly = x(5) / 100;
m = 30;
Kx = 1320; Ky = 1320 * 90.0;
wx = (Kx / m)^0.5;
mt = 1.5 * 2 / 2 / 2;
Lx = 1;
Cx = 2 * 0.025 * 4 * (Kx / m)^0.5 * m;
Cy = 2 * 0.025 * 4 * (Ky / m)^0.5 * m;
% This script is used to run a genetic algorithm to optimize the parameters of a nonlinear damping system model

clear % Clear the workspace
clc   % Clear the command window

% Define the parameters for the system
A = eye(6); % Define a 5x5 identity matrix

% Set the bounds for the optimization variables
b = [65; 290; 200; 200; 200; 200];
UB = [65; 290; 200; 200; 200; 200];
lb = [48; 215; 30; 50; 20; 20];
LB = [48; 215; 30; 50; 20; 20];

% Run the genetic algorithm to optimize the parameters using the TMD_nonlineardamploop function
[x, fval, exitflag] = ga(@TMD_nonlineardamploop, 6, A, b, [], [], LB, UB, [], [1, 2, 3, 4, 5, 6]);

    function y = TMD_nonlineardamploop(x)
        % This function calculates the response of a nonlinear damping system model
        % Inputs:
        % - x: Vector of optimization variables containing parameters for the system
        % Outputs:
        % - y: Maximum displacement of the system
        
        if ~isvector(x)
            error('Input must be a vector');
        end
        
        % Extract the optimization variables
        Kxt = x(1);
        Kyt = x(2);
        Kzt = x(3);
        Kisayx = x(4) / 1000;
        Kisayy = x(5) / 1000;
        Kisayz = x(6) / 1000;
        
        % Define system parameters
        Ly = x(5) / 100;Lz=x(5)/100
        m = 30;
        Kx = 1320; Ky = 1320 * 90.0;Kz=1320*180;
        wx = (Kx / m)^0.5;
        mt = 1.5 * 2 / 2 / 2;
        Lx = 1;
        Cx = 2 * 0.025 * 4 * (Kx / m)^0.5 * m;
        Cy = 2 * 0.025 * 4 * (Ky / m)^0.5 * m;
        Cz = 2*0.025*4*(Kz/m)^0.5*m;
        % Define the mass, stiffness, and damping matrices
        M = [m 0 0 0; 0 m 0 0; 0 0 mt 0; 0 0 0 mt; 0 0 0 mt];
        K = [Kx + Kxt 0 -Kxt 0; 0 Ky + Kyt 0 -Kyt; 0 Kz + Kzt 0 -Kzt; -Kxt 0 Kxt 0; 0 -Kyt 0 Kyt; 0 -Kzt 0 Kzt];
        C = [Cx + Cxt 0 -Cxt 0; 0 Cy + Cyt 0 -Cyt; Cz + Czt 0 0 -Czt; -Cyt; -Cxt 0 Cxt 0; 0 -Cyt 0 Cyt; 0 -Czt 0 Czt];
        
        ...
            
        % Run the nonlinear simulation and store the results
        non_linansw = [C_MMM1', MMM(:,1), MMM(:,2), MMM(:,3)];
        
        % Return the maximum displacement of the system
        y = max(max([non_linansw(:,2), non_linansw(:,3)]));
    end% This script is used to run a genetic algorithm to optimize the parameters of a nonlinear damping system model

clear % Clear the workspace
clc   % Clear the command window

% Define the parameters for the system
A = eye(6); % Define a 5x5 identity matrix

% Set the bounds for the optimization variables
b = [65; 290; 200; 200; 200; 200];
UB = [65; 290; 200; 200; 200; 200];
lb = [48; 215; 30; 50; 20; 20];
LB = [48; 215; 30; 50; 20; 20];

% Run the genetic algorithm to optimize the parameters using the TMD_nonlineardamploop function
[x, fval, exitflag] = ga(@TMD_nonlineardamploop, 6, A, b, [], [], LB, UB, [], [1, 2, 3, 4, 5, 6]);

    function y = TMD_nonlineardamploop(x)

The nested function name 'TMD_nonlineardamploop' must not be reused in the same scope.

        % This function calculates the response of a nonlinear damping system model
        % Inputs:
        % - x: Vector of optimization variables containing parameters for the system
        % Outputs:
        % - y: Maximum displacement of the system
        
        if ~isvector(x)
            error('Input must be a vector');
        end
        
        % Extract the optimization variables
        Kxt = x(1);
        Kyt = x(2);
        Kzt = x(3);
        Kisayx = x(4) / 1000;
        Kisayy = x(5) / 1000;
        Kisayz = x(6) / 1000;
        
        % Define system parameters
        Ly = x(5) / 100;
        m = 30;
        Kx = 1320; Ky = 1320 * 90.0;Kz=1320*180;
        wx = (Kx / m)^0.5;
        mt = 1.5 * 2 / 2 / 2;
        Lx = 1;
        Cx = 2 * 0.025 * 4 * (Kx / m)^0.5 * m;
        Cy = 2 * 0.025 * 4 * (Ky / m)^0.5 * m;
        Cz=2*0.025*4*(Ky/m)^0.5*m;
        % Define the mass, stiffness, and damping matrices
        M = [m 0 0 0; 0 m 0 0; 0 0 mt 0; 0 0 0 mt; 0 0 0 mt];
        K = [Kx + Kxt 0 -Kxt 0; 0 Ky + Kyt 0 -Kyt; 0 Kz + Kzt 0 -Kzt; -Kxt 0 Kxt 0; 0 -Kyt 0 Kyt; 0 -Kzt 0 Kzt];
        C = [Cx + Cxt 0 -Cxt 0; 0 Cy + Cyt 0 -Cyt; Cz + Czt 0 0 -Czt; -Cyt; -Cxt 0 Cxt 0; 0 -Cyt 0 Cyt; 0 -Czt 0 Czt];
        
        ...
            
        % Run the nonlinear simulation and store the results
        non_linansw = [C_MMM1', MMM(:,1), MMM(:,2), MMM(:,3)];
        
        % Return the maximum displacement of the system
        y = max(max([non_linansw(:,2), non_linansw(:,3)]));
    end
% Define the mass, stiffness, and damping matrices
M = [m 0 0 0; 0 m 0 0; 0 0 mt 0; 0 0 0 mt; 0 0 0 mt];
K = [Kx + Kxt 0 -Kxt 0; 0 Ky + Kyt 0 -Kyt; 0 Kz + Kzt 0 -Kzt; -Kxt 0 Kxt 0; 0 -Kyt 0 Kyt; 0 -Kzt 0 Kzt];
C = [Cx + Cxt 0 -Cxt 0; 0 Cy + Cyt 0 -Cyt; Cz + Czt 0 0 -Czt; -Cyt; -Cxt 0 Cxt 0; 0 -Cyt 0 Cyt; 0 -Czt 0 Czt];

...
    
% Run the nonlinear simulation and store the results
non_linansw = [C_MMM1', MMM(:,1), MMM(:,2), MMM(:,3)];

% Return the maximum displacement of the system
y = max(max([non_linansw(:,2), non_linansw(:,3)]));
end

[Doha Ali]

can you give the graph of the optimization?