fuzzpid.m

是一个模糊PID控制例子,控制对象为一个直升机俯仰轴的角度控制,数学模型为二阶传递函数.

%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',[-0.54,0.54]);                       %Parameter ec
a=addmf(a,'input',2,'NB','zmf',[-0.54,-0.18]);
a=addmf(a,'input',2,'NM','trimf',[-0.54,-0.36,0]);
a=addmf(a,'input',2,'NS','trimf',[-0.54,-0.18,0.18]);
a=addmf(a,'input',2,'Z','trimf',[-0.36,0,0.36]);
a=addmf(a,'input',2,'PS','trimf',[-0.18,0.18,0.54]);
a=addmf(a,'input',2,'PM','trimf',[0,0.36,0.54]);
a=addmf(a,'input',2,'PB','smf',[0.18,0.54]);

a=addvar(a,'output','kp',[-30,30]);                   %Parameter kp
a=addmf(a,'output',1,'NB','zmf',[-30,-10]);
a=addmf(a,'output',1,'NM','trimf',[-30,-20,0]);
a=addmf(a,'output',1,'NS','trimf',[-30,-10,10]);
a=addmf(a,'output',1,'Z','trimf',[-20,0,20]);
a=addmf(a,'output',1,'PS','trimf',[-10,10,30]);
a=addmf(a,'output',1,'PM','trimf',[0,20,30]);
a=addmf(a,'output',1,'PB','smf',[10,30]);


a=addvar(a,'output','ki',[-75,75]);                   %Parameter ki
a=addmf(a,'output',2,'NB','zmf',[-75,-25]);
a=addmf(a,'output',2,'NM','trimf',[-75,-50,0]);
a=addmf(a,'output',2,'NS','trimf',[-75,-25,25]);
a=addmf(a,'output',2,'Z','trimf',[-50,0,50]);
a=addmf(a,'output',2,'PS','trimf',[-25,25,75]);
a=addmf(a,'output',2,'PM','trimf',[0,50,75]);
a=addmf(a,'output',2,'PB','smf',[25,75]);

a=addvar(a,'output','kd',[-0.6,0.6]);                   %Parameter kd
a=addmf(a,'output',3,'NB','zmf',[-0.6,-0.2]);
a=addmf(a,'output',3,'NM','trimf',[-0.6,-0.4,0]);
a=addmf(a,'output',3,'NS','trimf',[-0.6,-0.2,0.2]);
a=addmf(a,'output',3,'Z','trimf',[-0.4,0,0.4]);
a=addmf(a,'output',3,'PS','trimf',[-0.2,0.2,0.6]);
a=addmf(a,'output',3,'PM','trimf',[0,0.4,0.6]);
a=addmf(a,'output',3,'PB','smf',[0.2,0.6]);


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];
       
a=addrule(a,rulelist);
a=setfis(a,'DefuzzMethod','centroid');
writefis(a,'fuzzpid');

a=readfis('fuzzpid');

%PID Controller
%ts=0.001;
%sys=tf(5.235e005,[1,87.35,1.047e004,0]);
%dsys=c2d(sys,ts,'tustin');
%[num,den]=tfdata(dsys,'v');

ts=0.01;
sys=tf(8.761,[1,4.185,8.761]);  
dsys=c2d(sys,ts,'tustin');
[num,den]=tfdata(dsys,'v');





u_1=0.0;u_2=0.0;

y_1=0;y_2=0;

x=[0,0,0]';

error_1=0;
e_1=0.0;
ec_1=0.0;

kp0=0.40;
kd0=1.0;
ki0=0.0;

for k=1:1:500
time(k)=k*ts;

rin(k)=1;
%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);

if k==300     % Adding disturbance(1.0v at time 0.3s)
   u(k)=u(k)+1.0;
end
if u(k)>=10
   u(k)=10;
end
if u(k)<=-10
   u(k)=-10;
end
yout(k)=-den(2)*y_1-den(3)*y_2+num(2)*u_1+num(3)*u_2;

%yout(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;
error(k)=rin(k)-yout(k);
%%%%%%%%%%%%%%Return of PID parameters%%%%%%%%%%%%%%%
   
   u_2=u_1;
   u_1=u(k);
   
 
   y_2=y_1;
   y_1=yout(k);
   
   x(1)=error(k);                % Calculating P
   x(2)=error(k)-error_1;        % Calculating D
   x(3)=x(3)+error(k);           % Calculating I

   e_1=x(1);
   ec_1=x(2);
   
   error_2=error_1;
   error_1=error(k);
end


%showrule(a)
kp(500)
ki(500)
kd(500)
figure(1);plot(time,rin,'b',time,yout,'r');
xlabel('time(s)');ylabel('rin,yout');
grid on
figure(2);plot(time,kp,'r');
xlabel('time(s)');ylabel('kp');
figure(3);plot(time,ki,'r');
xlabel('time(s)');ylabel('ki');
figure(4);plot(time,kd,'r');
xlabel('time(s)');ylabel('kd');