模糊自适应整定PID控制matlab仿真程序(刘金锟-先进P

1、这个例子的程序百度文库里有很多版本，但我下了很多都有错误，运行不了。以下程序我一字一字的敲出来的，已经成功运行，绝对无误。仿真实例，被控对象为(s=采样时间为1ms，采用模糊PID控制进行阶跃响应，在第300个采样时间时控制器输出加1.0的干扰，相应的运行结果如图113所示。仿真程序如下：将以下程序保存为fuzzypid.m文件，即可得到仿真结果。%fuzzy tunning PID controlclear all;clear all;a=newfis('fuzzpid'a=addvar(a,'input','e',-3,3; %paramet

2、er ea=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',&

3、#39;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 eca=addmf(a,'input',2,'NB','zmf',-3,-1;a=addmf(a,'input',2,'NM&

4、#39;,'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,'i

5、nput',2,'PB','smf',1,3;a=addvar(a,'output','kp',-0.3,0.3; %parameter kpa=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'

6、,-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,&#

7、39;output','ki',-0.06,0.06; %parameter kia=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,

8、9;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; %par

9、ameter kda=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,'

10、;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

11、 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

12、 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

13、','mom'writefis(a,'fuzzpid'a=readfis('fuzzpid'%PID controllerts=0.001;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=

14、0.0;for k=1:1:500time(k=k*ts;rin(k=1;%using fuzzy inference to tunning PIDk_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 0.3su(k=u(k+1.0;endif u(k>=10u(k=10;endif u(k<=-10u(k=-10;end yout(k=-

15、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 Px(2=error(k-error_1; %calculating Dx(3=x(3+error(k; %calculating De_1=x(1;ec_1=x(2;error_2=error_1;error_

16、1=error(k;endshowrule(afigure(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'xla