模糊自适应整定PID控制matlab仿真程序(刘金锟-先进P概要

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,523500(s=:1.0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 con trolclear all;clear all;a=newfis( fuzzpid;a=addvar(a, in put，e,-3,3; %parameter ea=addmf(a, i

2、nput ,1,NB ,zmf，-3,-1;a=addmf(a, in put ,1,NM ,trimf，-3,-2,0;a=addmf(a, in put ,1,NS,trimf，-3,-1,1;a=addmf(a, in put ,1,Z,trimf，-2,0,2;a=addmf(a,input ,1,PS,trimf，-1,1,3;a=addmf(a, in put ,1,PM ,trimf ,0,2,3;a=addmf(a, input ,1,PB,smf ,1,3;a=addvar(a, in put ,ec,-3,3; %parameter eca=addmf(a, input ,

3、2,NB ,zmf，-3,-1;a=addmf(a, input ,2,NM ,trimf，-3,-2,0;a=addmf(a, in put ,2,NS,trimf，-3,-1,1;a=addmf(a, in put ,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

4、 ,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，-0.06,0.0

5、6; %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,ou

6、tput,2, PB,smf,0.02,0.06; 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

7、(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 51 6 417 421 72 2 72 3 62 4 52 5 52 6 427 331 63 2 63 3 63 4 53 5 43 6 337 341 64 2 64 3 54 4 44 5 34 6 247 251 55 2 55 3 45 4 33 1 1 1;4 2 1 1;4 5 1 1;1 5 1 1;1 3 1 1;2 1 1 1;3 2 1 1;3 2 1 1;4 3 1 1;4 4 1

8、 1;1 4 1 1;2 3 1 1;3 2 1 1;3 2 1 1;4 3 1 1;5 3 1 1;5 4 1 1;2 4 1 1;2 3 1 1;3 3 1 1;4 3 1 1;5 3 1 1;6 3 1 1;6 4 1 1;2 4 1 1;3 4 1 1;4 4 1 1;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

9、;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 ,mom;writefis(a, fuzzpid;a=readfis( fuzzpid;%PID con trollerts=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=;y_2=o;y_3=o;x=0,0,0： error_1=0;e_仁 0.0;ec_仁 0.0;kp0=0.40;kd0=1.0;ki0=0.0;for k=1:1:500time(k=k*ts;rin (k=1;%us ing 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