fuzzypid.m

模糊pid控制方面的资料

%Fuzzy Tunning PID Control
clear all;
close all;
a=newfis('fuzzpud');                        %创建新的模糊推理系统（FIS）
a=addvar(a,'input','e',[-3,3]);            %Parameter e   向模糊推理系统添加语言变量
a=addmf(a,'input',1,'NB','zmf',[-3,-1]);       % 向模糊推理系统的语言变量添加隶属度函数，zmf指z-型 隶属度函数,trimf指三角形隶属度函数
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',[0.021,0.06]);

a=addvar(a,'output','kd',[-3,3]);            %Parameter Kd
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;               %rulelist是一个矩阵,每一行为一条规则,他们之间是ALSO的关系
          1 2 7 1 3 1 1;               %假定该FIS有N个输入和M个书橱，则每行有N+M+2个元素，前N个数分别表示N个输入变量的某一个语言名称的index
          1 3 6 2 1 1 1;               %没有的话用0表示，后面两个分别表示该条规则的权重和各条件的关系，1表示AND，2表示OR
          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);                  %向模糊推理系统（FIS）的语言变量添加规则
 a=setfis(a,'DefuzzMethod','centroid');   %得到模糊系统的属性
 writefis(a,'fuzzpid');                    % 保存FIS到磁盘上
 
 a=readfis('fuzzpid');                     % 从磁盘装入一个FIS 
 
 %PID Controller
 ts=0.001;                                %采样时间
 num=[523500];
 den=[1,87.35,10470,0];
 sys=tf(num,den);
 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=1:1:500
     time(k)=k*ts;
     
     rin(k)=1;            %输入信号为阶跃信号
     %Using fuzzy inference to tunning PID
     k_pid=evalfis([e_1,ec_1],a);                   %给定输入，得到输出，即进行模糊推理
     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-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');
   figure(7);
  plotmf(a,'input',1);
   figure(8);
    plotmf(a,'input',2);
     figure(9);
      plotmf(a,'output',1);
    figure(10);
      plotmf(a,'output',2);
      figure(11);
      plotmf(a,'output',3);
      plotfis(a);
      fuzzy fuzzpid