ode求解常微分方程如何获得某个点的数值解
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function dx = odefun(t,x)
ki1= 13.0;
ki2= 0.0;
kp11= 3.70e+04;
kp12= 673;
kp21= 1.36e+03;
kp22= 46;
ktal= 2.5;
kd= 1.0e-04;
hp1 = 101500000;
hp2 = 83000000;
dx = zeros(13,1);
dx(1) =ktal.*(x(5)+x(6)).*x(2)-ki1.*x(1).*x(3)-ki2.*x(1).*x(4);
dx(2) =ktal.*x(2).*(x(7)+x(8));
dx(3) =(ki1.*x(1)+kp11.*x(5)+kp21.*x(6)).*x(3);
dx(4) =(ki2.*x(1)+kp12.*x(5)+kp22.*x(6)).*x(4);
dx(5) =ki1.*x(1).*x(3)+kp21.*x(6).*x(3)-kp12.*x(5).*x(4)-(ktal.*x(2)+kd).*x(5);
dx(6) =ki2.*x(1).*x(4)+kp12.*x(5).*x(4)-kp21.*x(6).*x(3)-(ktal.*x(2)+kd).*x(6);
dx(7) =ki1.*x(1).*x(3)+kp11.*x(5).*x(3)+kp21.*(x(8)+x(6)).*x(3)-kp12.*x(7).*x(4)-(ktal.*x(2)+kd).*x(7);
dx(8) =ki2.*x(1).*x(4)+kp22.*x(6).*x(4)+kp12.*(x(7)+x(5)).*x(4)-kp21.*x(8).*x(3)-(ktal.*x(2)+kd).*x(8);
dx(9) =ki1.*x(1).*x(3)+kp11.*(2.*x(7)+x(5)).*x(3)+kp21.*(x(10)+2.*x(8)+x(6)).*x(3)-kp12.*x(9).*x(4)-(ktal.*x(2)+kd).*x(9);
dx(10) =ki2.*x(1).*x(4)+kp22.*(2.*x(8)+x(6)).*x(4)+kp12.*(x(9)+2.*x(7)+x(5)).*x(4)-kp21.*x(10).*x(3)-(ktal.*x(2)+kd).*x(10);
dx(11) =(ktal.*x(2)+kd).*(x(5)+x(6));
dx(12) =(ktal.*x(2)+kd).*(x(7)+x(8));
dx(13) =(ktal.*x(2)+kd).*(x(9)+x(10));
end
clear
clc
tspan=[0,1200];
y0=[2e-5,0.04,0.1524,1.0194,0,0,0,0,0,0,0,0,0];
[T,X] = ode45(@odefun,tspan,y0);
plot(T,X(:,1),'-',T,X(:,2),'-.',T,X(:,3),'.')
legend('x','y','z')
%mex(filename.c,'-compatibleArrayDims')
我的代码如上,但在点击运行后,约10分钟后报错
今天重新跑,运行二十分钟后一直没反应
我的疑问:
1.我的文件是否真的这么大,需要占用这么大数据量
2.网上查到的用例都是绘图,请问十三个未知数如何绘图
3.实际上我不关心过程,只想知道t=1200时,各自变量的数值
1 Comment
Dyuman Joshi
on 24 Jan 2024
I am not sure what you are trying to solve.
Could you please share which equation (or system of equations) you are trying to solve?
I don't see a relation between the error showed and the code posted.
Answers (1)
Varun
on 23 Jan 2024
Hey! Here are some things you can try out:
- Go to MATLAB -> Preferences -> Workspace -> MATLAB array size limit and set it to 100%.This will help you utilize all the RAM available on your device.
- Refer to the following documentation: https://www.mathworks.com/help/matlab/large-files-and-big-data.html. This will guide to a bunch of alternatives supported by MATLAB that you can employ as per your usecase.
Hope this helps!
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