Using fminsearch() for MSD system
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Gurkaran Singh
el 26 de Sept. de 2022
Editada: Gurkaran Singh
el 26 de Sept. de 2022
Hi guys, i am trying to optimize the mass damper system by choosing the optimal values of k2 and c2. I am getting so many errors while using fminsearch(). I am sharing the code below which is providing output for values of x1 and x2 (displacements of 2 masses). Our goal is to minimize x1 after 300s. It would be great if someone can help me modifying this code ofr fminsearch please.
In the code, values of k2 and c2 are selected manually but we need to optimize them using fminsearch()
clc
clear all
close all
tspan = [0:0.1:400]; %observing system's behaviour from 0-400 seconds
x0 = [0;0;0;0]; % as m1 and m2 are at rest at t=0.
%x1(0),x2(0),vel_m1(0) and vel_m2(0)
[t,x] = ode45(@odefun, tspan, x0); %odefun is the name of the function
plot(t,x(:,1)) %first degree
hold on
plot(t,x(:,2)) %second degree
legend('x1','x2')
xlabel('time')
ylabel('displacement')
function dxdt= odefun(t,x) %creating derivative functions
m1=50000; % given in the question
m2=1000; % 2 percent mass of m1
k1=500; % given in the question.
k2=50; % manually selected value to minimize x1
c2=400; % manually selected value to minimize x1
if t<=0.1 %Fd occurs at m1 only for first 100 ms
Fd=1000;
else
Fd=0;
end
%initializing column vector dxdt function
dxdt=zeros(4,1);
dxdt(1)=x(3); %equation 1
dxdt(2)=x(4); %equation 2
dxdt(3)=1/m1*(-(k1+k2)*x(1)+k2*x(2)-c2*(x(4)-x(3))+Fd); %equation 3
dxdt(4)=1/m2*(k2*x(1)-k2*(x(2))+c2*(x(3))-c2*(x(4))); %equation 4
end
2 comentarios
Alan Stevens
el 26 de Sept. de 2022
What do you mean by optimize/minimize x1? x1 varies in time; at what time do you want it minimized?
Respuesta aceptada
Torsten
el 26 de Sept. de 2022
Editada: Torsten
el 26 de Sept. de 2022
p0 = [50 400];
p = fminsearch(@fun,p0)
function objective = fun(p)
k2 = p(1);
c2 = p(2);
%tspan = [0,0.3]; %observing system's behaviour from 0-400 seconds
x0 = [0;0;0;0]; % as m1 and m2 are at rest at t=0.
%x1(0),x2(0),vel_m1(0) and vel_m2(0)
tspan = [0,0.1];
iflag = 1;
[t,x] = ode45(@(t,x)odefun(t,x,k2,c2,iflag), tspan, x0); %odefun is the name of the function
tspan = [0.1,0.3];
x0 = x(end,:);
iflag = 2;
[t,x] = ode45(@(t,x)odefun(t,x,k2,c2,iflag), tspan, x0); %odefun is the name of the function
objective = x(end,1);
end
function dxdt= odefun(t,x,k2,c2,iflag) %creating derivative functions
m1=50000; % given in the question
m2=1000; % 2 percent mass of m1
k1=500; % given in the question.
%k2=50; % manually selected value to minimize x1
%c2=400; % manually selected value to minimize x1
if iflag==1
Fd = 1000;
elseif iflag==2
Fd = 0.0;
end
%if t<=0.1 %Fd occurs at m1 only for first 100 ms
% Fd=1000;
%else
% Fd=0;
%end
%initializing column vector dxdt function
dxdt=zeros(4,1);
dxdt(1)=x(3); %equation 1
dxdt(2)=x(4); %equation 2
dxdt(3)=1/m1*(-(k1+k2)*x(1)+k2*x(2)-c2*(x(4)-x(3))+Fd); %equation 3
dxdt(4)=1/m2*(k2*x(1)-k2*(x(2))+c2*(x(3))-c2*(x(4))); %equation 4
end
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