fuzzpid.m

用matlab 来仿真模糊pid控制器

clear all;
close all;
a=newfis('fuzzpid');
f1=1;
a=addvar(a,'input','e',[-3*f1,3*f1]);             
a=addmf(a,'input',1,'NB','zmf',[-3*f1,-1*f1]);
a=addmf(a,'input',1,'NM','trimf',[-3*f1,-2*f1,0]);
a=addmf(a,'input',1,'NS','trimf',[-3*f1,-1*f1,1*f1]);
a=addmf(a,'input',1,'Z','trimf',[-2*f1,0,2*f1]);
a=addmf(a,'input',1,'PS','trimf',[-1*f1,1*f1,3*f1]);
a=addmf(a,'input',1,'PM','trimf',[0,2*f1,3*f1]);
a=addmf(a,'input',1,'PB','smf',[1*f1,3*f1]);
f2=1;
a=addvar(a,'input','ec',[-3*f2,3*f2]);
a=addmf(a,'input',2,'NB','zmf',[-3*f2,-1*f2]);
a=addmf(a,'input',2,'NM','trimf',[-3*f2,-2*f2,0]);
a=addmf(a,'input',2,'NS','trimf',[-3*f2,-1*f2,1*f2]);
a=addmf(a,'input',2,'Z','trimf',[-2*f2,0,2*f2]);
a=addmf(a,'input',2,'PS','trimf',[-1*f2,1*f2,3*f2]);
a=addmf(a,'input',2,'PM','trimf',[0,2*f2,3*f2]);
a=addmf(a,'input',2,'PB','smf',[1*f2,3*f2]);

a=addvar(a,'output','kp',[-0.3,0.3]);
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]);
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]);
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];
          
      a=addrule(a,rulelist);%给模糊推理系统FIS的语言变量添加规
      a=setfis(a,'DefuzzMethod','centroid');%设置模糊系统的属性
      writefis(a,'fuzzpid');%保存FIS
      a=readfis('fuzzpid');%从磁盘装入一个FIS
      
      
      %PID Controller
      ts=0.01;
      sys=tf(5.235e005,[1,87.35,1.047e004,0]);
      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=[0,0,0]';
      
      error_1=0;
      e_1=0.0;
      ec_1=0.0;
      
      Kp0=0.40;
      Kd0=1.0;
      Ki0=0.0;
      
      for k=1:1:1000
          time(k)=k*ts;
          
        % rin(k)=0.5*sin(1*pi*k*ts);
         rin(k)=1;
         
         
   %Using fuzzy inference to tuning PID
         k_pid=evalfis([e_1,ec_1],a);%完成模糊推理计算
         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)>=3
             u(k)=3;
         end
         if u(k)<=-3
             u(k)=-3;
         end
         
         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_3=u_2;
         u_2=u_1;
         u_1=u(k);
         
         y_3=y_2;
         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)
     figure(1);plot(time,rin,'b',time,yout,'r');
     xlabel('time(s)');ylabel('rin,yout');
     figure(2);plot(time,error,'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');