多变量系统辨识matlab程序.docx

1、多变量系统辨识matlab程序多变量系统辨识matlab程序y(i=0.05129*u1_1+0.0418;u1_3=u1_2;u1_2=u1_1;u1_1; u2_3=u2_2;u2_2=u2_1;u2_1;y_3=y_2;y_2=y_1;y_1=y(i; r_3=r_2;r_2=r_1;r_1=r(i;end;plot(time,y,b;holdon;xi=y;savesub.y(i=0.05129*u1_1+0.0418*u2_1+0.6386*y_1+0.06268*u1_2+0.0346*u2_2 -0.1179*y_2-0.004184*u1_3-0.00218*u2_3+0.00

2、6738*y_3+0.091*r_1-0.114*r _2+0.0509*r_3;u1_3=u1_2;u1_2=u1_1;u1_1=u1(i;u2_3=u2_2;u2_2=u2_1;u2_1=u2(i;y_3=y_2;y_2=y_1;y_1=y(i;r_3=r_2;r_2=r_1;r_1=r(i;endplot(time,y,bhold onxi=y;save sub.txt xi ascii程序5clear%CRA模型基于模型阶次递增的辨识。clcclose allz=load(sub.txt;u1=load(prbs1.txt;u2=load(prbs2.txt;for i=1:1:100

3、H(i,:=u1(20+i-1 u2(20+i-1 -1*z(20+i-1;endtheta=(1e-3*ones(3,1;P=(1e8*eye(3;for i=1:1:100K=P*H(i,:./(H(i,:*P*H(i,:+1;theta=theta+K*(z(i+20-H(i,:*theta;P=(eye(3-K*H(i,:*P;endtheta1=thetaH1=H;J(1=(z(21:120-H1*theta1*(z(21:120-H1*theta1; ZZ=inv(H1*H1;%*for n=2:1:10for i=1:1:100H2(i,:=u1(20+i-n u2(20+i-n

4、 -1*z(20+i-n;endB=inv(H2*H2-H2*H1*ZZ*H1*H2;A=ZZ*H1*H2*B;theta2=B*H2*(z(21:120-H1*theta1;theta1=theta1-A*H2*(z(21:120-H1*theta1;theta1=theta1;theta2ZZ1=ZZ+A*H2*H1*ZZ -A;ZZ2=-A B;ZZ=ZZ1;ZZ2;J(n=(z(21:120-H1*theta1*(z(21:120-H1*theta1; F(n-1=(J(n-1-J(n/2/(J(n/(100-2*n;time(n-1=n;TEST(n-1=3;endplot(time

5、,F,r-*,time,TESTtitle(F统计值随系统阶次的变化xlabel(系统阶次ylabel(F统计值legend(F(2(n_2-n_1,100-2n_2,F(2,100程序6clear%*CAR模型最佳辨识的验证,同时获取CARMA模型的残差序列,存于error.txt中。clcu1=load(prbs1.txt;u2=load(prbs2.txt;z=load(sub.txtu1_6=0;u1_5=0;u1_4=0;u1_1=0;u1_2=0;u1_3=0;u2_6=0;u2_5=0;u2_4=0;u2_1=0;u2_2=0;u2_3=0;y_6=0;y_5=0;y_4=0;y

6、_1=0;y_2=0;y_3=0;r_1=0;r_2=0;r_3=0;for i=1:1:120time(i=i;y(i=0.0496*u1_1+0.0417*u2_1-0.6724*y_1+0.1300*u1_2+0.0902*u2_2-0. 4219*y_2+0.1352*u1_3+0.0911*u2_3-0.1887*y_3+0.1032*u1_4+0.0707*u2_4+-0.0188*y_4+0.0639*u1_5+0.0401*u2_5+00.1125*y_5+ 0.0210*u1_6+0.0132*u2 _6-0.0101*y_6;u1_6=u1_5;u1_5=u1_4;u1_4

7、=u1_3;u1_3=u1_2;u1_2=u1_1;u1_1=u1(i;u2_6=u2_5;u2_5=u2_4;u2_4=u2_3;u2_3=u2_2;u2_2=u2_1;u2_1=u2(i;y_6=y_5;y_5=y_4;y_4=y_3;y_3=y_2;y_2=y_1;y_1=y(i;endplot(time,y,ghold one=z-y;save error.txt e ascii程序7clear%子模型基于模型阶次递增的辨识。clcclose allz=load(sub.txt;u1=load(prbs1.txt;u2=load(prbs2.txt;e=load(error.txt;f

8、or i=1:1:100endtheta=(1e-3*ones(4,1;P=(1e8*eye(4;for i=1:1:100K=P*H(i,:./(H(i,:*P*H(i,:+1;theta=theta+K*(z(i+20-H(i,:*theta;P=(eye(4-K*H(i,:*P;endtheta1=thetaH1=H;J(1=(z(21:120-H1*theta1*(z(21:120-H1*theta1;ZZ=inv(H1*H1;%*for n=2:1:10for i=1:1:100H2(i,:=u1(20+i-n u2(20+i-n -1*z(20+i-n e(20+i-n; endB

9、=inv(H2*H2-H2*H1*ZZ*H1*H2;A=ZZ*H1*H2*B;theta2=B*H2*(z(21:120-H1*theta1;theta1=theta1-A*H2*(z(21:120-H1*theta1;theta1=theta1;theta2ZZ1=ZZ+A*H2*H1*ZZ -A;ZZ2=-A B;ZZ=ZZ1;ZZ2;H1=H1 H2;J(n=(z(21:120-H1*theta1*(z(21:120-H1*theta1;F(n-1=(J(n-1-J(n/3/(J(n/(100-3*n;time(n-1=n;TEST(n-1=3;endplot(time,F,r-*,ti

10、me,TESTtitle(F统计值随系统阶次的变化xlabel(系统阶次ylabel(F统计值legend(F(2(n_2-n_1,100-2n_2,F(2,100程序8clearclcu1=load(prbs1.txt;u2=load(prbs2.txt;z=load(sub.txt;e=load(error.txt;u1_1=0;u1_2=0;u1_3=0;u1_4=0;y_1=0;y_2=0;y_3=0;y_4=0;e_4=0;e_1=0;e_2=0;e_3=0;y1_1=0;y1_2=0;y1_3=0;y1_4=0;y2_1=0;y2_2=0;y2_3=0;y2_4=0;r_1=0;r

11、_2=0;r_3=0;for i=1:1:120time(i=i;y(i=0.0507*u1_1+0.0426*u2_1-0.8329*y_1+0.2335*e_1+0.1383*u1_2+0. 0974*u2_2-0.2791*y_2-0.1006*e_2+0.1437*u1_3+0.0956*u2_3+0.4623*y_3-0. 7050*e_3+0.0654*u1_4+0.0400*u2_4-0.0736*y_4-0.0502*e_4;y1(i=0.0507*u1_1-0.8329*y1_1+0.1383*u1_2-0.2791*y1_2+0.1437*u1_3 +0.4623*y1_3

12、+0.0654*u1_4-0.0736*y1_4;y2(i=0.0426*u2_1-0.8329*y2_1+0.0974*u2_2-0.2791*y2_2+0.0956*u2_3 +0.4623*y2_3+0.0400*u2_4-0.0736*y2_4;u1_4=u1_3;u1_3=u1_2;u1_2=u1_1;u1_1=u1(i;u2_4=u2_3;u2_3=u2_2;u2_2=u2_1;u2_1=u2(i;y_4=y_3;y_3=y_2;y_2=y_1;y_1=y(i;e_4=e_3;e_3=e_2;e_2=e_1;e_1=e(i;y1_4=y1_3;y1_3=y1_2;y1_2=y1_1

13、;y1_1=y1(i;y2_4=y2_3;y2_3=y2_2;y2_2=y2_1;y2_1=y2(i;endplot(time,y,m,time,y1+y2,khold onsave ssub1.txt y1 -asciisave ssub2.txt y2 ascii程序9clear%子子模型1的基于阶次递增的辨识。clc% close allz=load(ssub1.txt;u=load(prbs1.txt;for i=1:1:100H(i,:=u(20+i-1 -1*z(20+i-1;endtheta=(1e-3*ones(2,1;P=(1e8*eye(2;for i=1:1:100K=P

14、*H(i,:./(H(i,:*P*H(i,:+1; theta=theta+K*(z(i+20-H(i,:*theta;P=(eye(2-K*H(i,:*P;endtheta1=thetasigmaF(1=(z(21:120-H1*theta1*(z(21:120-H1*theta1/100; AIC (1=100*log10(sigmaF(1+2*(1+1;ZZ=inv(H1*H1;ZZ=inv(H1*H1;THETA=zeros(10,20;% THETA(2,:=theta1;%*for n=2:1:10for i=1:1:100H2(i,:=u(20+i-n -1*z(20+i-n;e

15、ndB=inv(H2*H2-H2*H1*ZZ*H1*H2;A=ZZ*H1*H2*B;theta2=B*H2*(z(21:120-H1*theta1;theta1=theta1-A*H2*(z(21:120-H1*theta1;theta1=theta1;theta2ZZ1=ZZ+A*H2*H1*ZZ -A;ZZ2=-A B; ZZ=ZZ1;ZZ2; H1=H1 H2; time(n-1=n; sigmaF(n=(z(21:120-H1*theta1*(z(21:120-H1*theta1/100; AIC (n-1=100*log10(sigmaF(n+2*(n+n; end plot(tim

16、e,AIC,r-* title(信息准则 AIC 值随系统阶次的变化 xlabel(系统阶次 ylabel(信息准则 AIC 值 程序 10 clear %子子模型 2 的基于阶次递增的辨识。 clc close all z=load(ssub2.txt; u=load(prbs2.txt; for i=1:1:100 H(i,:=u(20+i-1 -1*z(20+i-1; end theta=(1e-3*ones(2,1; P=(1e8*eye(2; for i=1:1:100 K=P*H(i,:./(H(i,:*P*H(i,:+1; theta=theta+K*(z(i+20-H(i,:*theta; P=(eye(2-K*H(i,:*P; end theta1=theta