基于matlab实现的弹簧振动系统模型程序(动态模型)

完整代码:

clear all;

%System data

m=1.0; zeta=0.01; omega0=1.0; Dt=1.0; f0=1.0;

x0=0.0; dotx0=0.0;

xmax=sqrt(x0^2+(dotx0/omega0)^2)+min([0.5*abs(f0)*Dt/(m*omega0) f0/omega0^2]);

omegad=omega0*sqrt(1-zeta^2);

dt0=0.1*pi/omega0; nstep=500;

a=0.70; b=0.70; r=0.35*a; fact=0.50/xmax;

xf0=0.5*[0 -a 0 a 0]';

yf0=[0 -b/4 -b/2 -3*b/4 -b]';

xd1=0.5*[-a -a a a]';

yd1=[-6*b 0 0 -6*b]';

xd2=0.5*[-0.8*a 0.8*a]';

yd2=[-3*b -3*b]';

xf0=[xf0

xf0

xf0

xf0

xf0

xf0];

yf0=[yf0

-b+yf0

-2*b+yf0

-3*b+yf0

-4*b+yf0

-5*b+yf0];

xf=[0

xf0

0];

xSQ=[-a 5*a 5*a -a -a]';

ySQ=[0 0 -2*r -2*r 0]';

xH=[-2000 2000]'; yH=[0 0]';

xx=x0;

tt=0;

set(gcf,'DoubleBuffer','on');

i=1;

t=i*dt0;

t0=min([t Dt]);

t1=t-t0;

h=exp(-zeta*omega0*t)*sin(omegad*t)/(m*omegad);

doth=exp(-zeta*omega0*t)*(cos(omegad*t)-zeta*omega0/omegad*sin(omegad*t))/m;

H=(1/m-doth-2*zeta*omega0*h)/omega0^2;

h1=exp(-zeta*omega0*t1)*sin(omegad*t1)/(m*omegad);

doth1=exp(-zeta*omega0*t1)*(cos(omegad*t1)-zeta*omega0/omegad*sin(omegad*t1))/m;

H1=(1/m-doth1-2*zeta*omega0*h1)/omega0^2;

if t>Dt

t2=t-Dt;

h2=exp(-zeta*omega0*t2)*sin(omegad*t2)/(m*omegad);

doth2=exp(-zeta*omega0*t2)*(cos(omegad*t2)-zeta*omega0/omegad*sin(omegad*t2))/m;

H2=(1/m-doth2-2*zeta*omega0*h2)/omega0^2;

else

H2=0;

end

x=-f0*H2+f0*(t0/m+h1-h+2*zeta*omega0*(H1-H))/(Dt*omega0^2);

x=x+exp(-zeta*omega0*t)*(x0*cos(omegad*t)+(dotx0+zeta*omega0*x0)*sin(omegad*t)/omegad);

tt=[tt

t];

xx=[xx

x];

x=fact*x;

yf=[0

-2*b+(1+x)*yf0

-6*b+(1+x)*yf0(size(yf0,1))];

clf;

figure(1);

subplot(2,1,1)

h1=plot(xH,yH,'r');

hold on

h2=plot(xH,yH-6*b+yf0(size(yf0,1))-r,'k');

h3=plot(xf,yf,'r');

h4=plot(4*a+xd1,-3*b+yd1,'r');

h5=plot(4*a*[1 1]',-3*b*[0 1]','r');

hej=yf(size(yf,1));

h6=plot(4*a+xd2,(-7*b+yf(size(yf,1))-hej)*ones(2,1),'r');

h7=plot(4*a*[1 1]',[-7*b+yf(size(yf,1))-hej yf(size(yf,1))]','r');

h8=plot(xSQ,yf(size(yf,1))+ySQ,'r');

hold off

axis([-2 5 -10*b+(1+fact*x0)*yf0(size(yf0,1))-2*r r]);

subplot(2,1,2)

h9=plot(xH,yH,'k');

hold on;

h10=plot(tt,-xx,'r');

hold off;

axis([ 0 nstep*dt0 -xmax xmax])

% start loop

for i=1:nstep

t=i*dt0;

t0=min([t Dt]);

t1=t-t0;

h=exp(-zeta*omega0*t)*sin(omegad*t)/(m*omegad);

doth=exp(-zeta*omega0*t)*(cos(omegad*t)-zeta*omega0/omegad*sin(omegad*t))/m;

H=(1/m-doth-2*zeta*omega0*h)/omega0^2;

h1=exp(-zeta*omega0*t1)*sin(omegad*t1)/(m*omegad);

doth1=exp(-zeta*omega0*t1)*(cos(omegad*t1)-zeta*omega0/omegad*sin(omegad*t1))/m;

H1=(1/m-doth1-2*zeta*omega0*h1)/omega0^2;

if t>Dt

t2=t-Dt;

h2=exp(-zeta*omega0*t2)*sin(omegad*t2)/(m*omegad);

doth2=exp(-zeta*omega0*t2)*(cos(omegad*t2)-zeta*omega0/omegad*sin(omegad*t2))/m;

H2=(1/m-doth2-2*zeta*omega0*h2)/omega0^2;

else

H2=0;

end

x=-f0*H2+f0*(t0/m+h1-h+2*zeta*omega0*(H1-H))/(Dt*omega0^2);

x=x+exp(-zeta*omega0*t)*(x0*cos(omegad*t)+(dotx0+zeta*omega0*x0)*sin(omegad*t)/omegad);

tt=[tt

t];

xx=[xx

x];

x=fact*x;

yf=[0

-2*b+(1+x)*yf0

-6*b+(1+x)*yf0(size(yf0,1))];

set(h3,'Xdata',xf);

set(h3,'Ydata',yf);

set(h4,'Xdata',4*a+xd1);

set(h4,'Ydata',-3*b+yd1);

set(h5,'Xdata',4*a*[1 1]');

set(h5,'Ydata',-3*b*[0 1]');

set(h6,'Xdata',4*a+xd2);

set(h6,'Ydata',(-7*b+yf(size(yf,1))-hej)*ones(2,1));

set(h7,'Xdata',4*a*[1 1]');

set(h7,'Ydata',[-7*b+yf(size(yf,1))-hej yf(size(yf,1))]');

set(h8,'Xdata',xSQ);

set(h8,'Ydata',yf(size(yf,1))+ySQ);

set(h10,'Xdata',tt);

set(h10,'Ydata',-xx);

pause(0.1)

end;

相关推荐
The hopes of the whole village6 小时前
matlab 绘图
开发语言·matlab·信息可视化
程高兴16 小时前
基于Matlab的车牌识别系统
开发语言·matlab
XuX0319 小时前
手搓雷达图(MATLAB)
matlab·贴图
freexyn1 天前
Matlab自学笔记五十一:(推荐)输入参数的数量和可变数量的输入
笔记·算法·matlab
不吃酸的柠檬1 天前
MATLAB 中的图形绘制
人工智能·机器学习·matlab
studyer_domi1 天前
Matlab 复合模糊PID
开发语言·matlab
DarrenPig2 天前
【新能源科学与技术】MATALB/Simulink小白教程(一)实验文档【新能源电力转换与控制仿真】
matlab·开源·github·simulink·交流
简简单单做算法2 天前
基于GA遗传优化TCN-BiGRU注意力机制网络模型的时间序列预测算法matlab仿真
matlab·tcn-bigru·时间序列预测·注意力机制·ga遗传优化
Cc小跟班2 天前
MATLAB小技巧记录(特殊符号、图例位置...)
开发语言·算法·matlab
随风飘摇的土木狗3 天前
【MATLAB第116期】基于MATLAB的NBRO-XGBoost的SHAP可解释回归模型(敏感性分析方法)
matlab·gsa·敏感性分析·特征排序·灵敏度分析·shap·可解释