📄 chap4_7b.m
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%Fuzzy Tunning PID Control
clear all;
close all;
a=newfis('fuzzpid');
a=addvar(a,'input','e',[-3,3]); %Parameter e
a=addmf(a,'input',1,'NB','zmf',[-3,-1]);
a=addmf(a,'input',1,'NM','trimf',[-3,-2,0]);
a=addmf(a,'input',1,'NS','trimf',[-3,-1,1]);
a=addmf(a,'input',1,'Z','trimf',[-2,0,2]);
a=addmf(a,'input',1,'PS','trimf',[-1,1,3]);
a=addmf(a,'input',1,'PM','trimf',[0,2,3]);
a=addmf(a,'input',1,'PB','smf',[1,3]);
a=addvar(a,'input','ec',[-3,3]); %Parameter ec
a=addmf(a,'input',2,'NB','zmf',[-3,-1]);
a=addmf(a,'input',2,'NM','trimf',[-3,-2,0]);
a=addmf(a,'input',2,'NS','trimf',[-3,-1,1]);
a=addmf(a,'input',2,'Z','trimf',[-2,0,2]);
a=addmf(a,'input',2,'PS','trimf',[-1,1,3]);
a=addmf(a,'input',2,'PM','trimf',[0,2,3]);
a=addmf(a,'input',2,'PB','smf',[1,3]);
a=addvar(a,'output','kp',[-0.3,0.3]); %Parameter kp
a=addmf(a,'output',1,'NB','zmf',[-0.3,-0.1]);
a=addmf(a,'output',1,'NM','trimf',[-0.3,-0.2,0]);
a=addmf(a,'output',1,'NS','trimf',[-0.3,-0.1,0.1]);
a=addmf(a,'output',1,'Z','trimf',[-0.2,0,0.2]);
a=addmf(a,'output',1,'PS','trimf',[-0.1,0.1,0.3]);
a=addmf(a,'output',1,'PM','trimf',[0,0.2,0.3]);
a=addmf(a,'output',1,'PB','smf',[0.1,0.3]);
a=addvar(a,'output','ki',[-0.06,0.06]); %Parameter ki
a=addmf(a,'output',2,'NB','zmf',[-0.06,-0.02]);
a=addmf(a,'output',2,'NM','trimf',[-0.06,-0.04,0]);
a=addmf(a,'output',2,'NS','trimf',[-0.06,-0.02,0.02]);
a=addmf(a,'output',2,'Z','trimf',[-0.04,0,0.04]);
a=addmf(a,'output',2,'PS','trimf',[-0.02,0.02,0.06]);
a=addmf(a,'output',2,'PM','trimf',[0,0.04,0.06]);
a=addmf(a,'output',2,'PB','smf',[0.02,0.06]);
% a=addvar(a,'output','kd',[-3,3]); %Parameter kp
% a=addmf(a,'output',3,'NB','zmf',[-3,-1]);
% a=addmf(a,'output',3,'NM','trimf',[-3,-2,0]);
% a=addmf(a,'output',3,'NS','trimf',[-3,-1,1]);
% a=addmf(a,'output',3,'Z','trimf',[-2,0,2]);
% a=addmf(a,'output',3,'PS','trimf',[-1,1,3]);
% a=addmf(a,'output',3,'PM','trimf',[0,2,3]);
% a=addmf(a,'output',3,'PB','smf',[1,3]);
% rulelist=[1 1 7 1 5 1 1;
% 1 2 7 1 3 1 1;
% 1 3 6 2 1 1 1;
% 1 4 6 2 1 1 1;
% 1 5 5 3 1 1 1;
% 1 6 4 4 2 1 1;
% 1 7 4 4 5 1 1;
%
% 2 1 7 1 5 1 1;
% 2 2 7 1 3 1 1;
% 2 3 6 2 1 1 1;
% 2 4 5 3 2 1 1;
% 2 5 5 3 2 1 1;
% 2 6 4 4 3 1 1;
% 2 7 3 4 4 1 1;
%
% 3 1 6 1 4 1 1;
% 3 2 6 2 3 1 1;
% 3 3 6 3 2 1 1;
% 3 4 5 3 2 1 1;
% 3 5 4 4 3 1 1;
% 3 6 3 5 3 1 1;
% 3 7 3 5 4 1 1;
%
% 4 1 6 2 4 1 1;
% 4 2 6 2 3 1 1;
% 4 3 5 3 3 1 1;
% 4 4 4 4 3 1 1;
% 4 5 3 5 3 1 1;
% 4 6 2 6 3 1 1;
% 4 7 2 6 4 1 1;
%
% 5 1 5 2 4 1 1;
% 5 2 5 3 4 1 1;
% 5 3 4 4 4 1 1;
% 5 4 3 5 4 1 1;
% 5 5 3 5 4 1 1;
% 5 6 2 6 4 1 1;
% 5 7 2 7 4 1 1;
%
% 6 1 5 4 7 1 1;
% 6 2 4 4 5 1 1;
% 6 3 3 5 5 1 1;
% 6 4 2 5 5 1 1;
% 6 5 2 6 5 1 1;
% 6 6 2 7 5 1 1;
% 6 7 1 7 7 1 1;
%
% 7 1 4 4 7 1 1;
% 7 2 4 4 6 1 1;
% 7 3 2 5 6 1 1;
% 7 4 2 6 6 1 1;
% 7 5 2 6 5 1 1;
% 7 6 1 7 5 1 1;
% 7 7 1 7 7 1 1];
rulelist=[1 1 7 1 1 1;
1 2 7 1 1 1;
1 3 6 2 1 1;
1 4 6 2 1 1;
1 5 5 3 1 1;
1 6 4 4 1 1;
1 7 4 4 1 1;
2 1 7 1 1 1;
2 2 7 1 1 1;
2 3 6 2 1 1;
2 4 5 3 1 1;
2 5 5 3 1 1;
2 6 4 4 1 1;
2 7 3 4 1 1;
3 1 6 1 1 1;
3 2 6 2 1 1;
3 3 6 3 1 1;
3 4 5 3 1 1;
3 5 4 4 1 1;
3 6 3 5 1 1;
3 7 3 5 1 1;
4 1 6 2 1 1;
4 2 6 2 1 1;
4 3 5 3 1 1;
4 4 4 4 1 1;
4 5 3 5 1 1;
4 6 2 6 1 1;
4 7 2 6 1 1;
5 1 5 2 1 1;
5 2 5 3 1 1;
5 3 4 4 1 1;
5 4 3 5 1 1;
5 5 3 5 1 1;
5 6 2 6 1 1;
5 7 2 7 1 1;
6 1 5 4 1 1;
6 2 4 4 1 1;
6 3 3 5 1 1;
6 4 2 5 1 1;
6 5 2 6 1 1;
6 6 2 7 1 1;
6 7 1 7 1 1;
7 1 4 4 1 1;
7 2 4 4 1 1;
7 3 2 5 1 1;
7 4 2 6 1 1;
7 5 2 6 1 1;
7 6 1 7 1 1;
7 7 1 7 1 1];
a=addrule(a,rulelist);
a=setfis(a,'DefuzzMethod','centroid');
writefis(a,'fuzzpid');
a=readfis('fuzzpid');
figure(1);
plotmf(a,'input',1);
figure(2);
plotmf(a,'input',2);
figure(3);
plotmf(a,'output',1);
figure(4);
plotmf(a,'output',2);
figure(5);
% plotmf(a,'output',3);
% figure(6);
plotfis(a);
fuzzy fuzzpid;
showrule(a);
ruleview fuzzpid;
ts=0.001;
% sys=tf(5.235e005,[1,87.35,1.047e004,0]);
sys=tf(72,[60,1]);
dsys=c2d(sys,ts,'tustin');
[num,den]=tfdata(dsys,'v');
u_1=0.0;u_2=0.0;u_3=0.0;
y_1=0;y_2=0;y_3=0;
x=[0,0]';
e_1=0;
ec_1=0;
kp0=0.40;
% kd0=1.0;
ki0=0.05;
for k=1:1:3000
time(k)=k*ts;
r(k)=sign(sin(2*pi*k*ts));
%Using fuzzy inference to tunning PID
k_pid=evalfis([e_1,ec_1],a);
kp(k)=kp0+k_pid(1);
ki(k)=ki0+k_pid(2);
% kd(k)=kd0+k_pid(3);
% u(k)=kp(k)*x(1)+kd(k)*x(2)+ki(k)*x(3);
u(k)=kp(k)*x(1)+ki(k)*x(2);
if k==300 % Adding disturbance(1.0v at time 0.3s)
u(k)=u(k)+1.0;
end
% y(k)=-den(2)*y_1-den(3)*y_2-den(4)*y_3+num(1)*u(k)+num(2)*u_1+num(3)*u_2+num(4)*u_3;
y(k)=-den(2)*y_1+num(1)*u(k)+num(2)*u_1;
e(k)=r(k)-y(k);
%%%%%%%%%%%%%%Return of PID parameters%%%%%%%%%%%%%%%
u_3=u_2;
u_2=u_1;
u_1=u(k);
y_3=y_2;
y_2=y_1;
y_1=y(k);
x(1)=e(k); % Calculating P
% x(2)=e(k)-e_1; % Calculating D
x(2)=x(2)+e(k)*ts; % Calculating I
ec_1=x(2);
e_2=e_1;
e_1=e(k);
end
figure
plot(r,'g')
figure(1);
plot(time,r,'b',time,y,'r');
xlabel('time(s)');ylabel('rin,yout');
figure(2);
plot(time,e,'r');
xlabel('time(s)');ylabel('error');
figure(3);
plot(time,u,'r');
xlabel('time(s)');ylabel('u');
figure(4);
plot(time,kp,'r');
xlabel('time(s)');ylabel('kp');
figure(5);
plot(time,ki,'r');
xlabel('time(s)');ylabel('ki');
figure(6);
% plot(time,kd,'r');
% xlabel('time(s)');ylabel('kd');⌨️ 快捷键说明
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