模糊控制PID設(shè)計(jì)大作業(yè)

1、精選優(yōu)質(zhì)文檔-傾情為你奉上參考教材中例子設(shè)計(jì)一包含了模糊技術(shù)與PID技術(shù)的混合智能控制器，其被控對(duì)象為：采樣時(shí)間為1ms，編寫matlab仿真程序，確定其在階躍輸入的響應(yīng)結(jié)果，并與經(jīng)典PID控制仿真結(jié)果相比較。要求詳細(xì)描述控制系統(tǒng)的設(shè)計(jì)，控制系統(tǒng)工作流程，模糊系統(tǒng)中的輸入輸出的隸屬函數(shù)設(shè)計(jì)及其采用的模糊規(guī)則，分析仿真結(jié)果并進(jìn)行總結(jié)。表1 kp的模糊規(guī)則表eckpeNBNMNSZOPSPMPBNBPBPBPMPMPSZOZONMPBPBPMPSPSZONSNSPMPMPMPSZONSNSZOPMPMPSZONSNMNMPSPSPSZONSNSNMNMPMPSZONSNMNMNMNBPBZOZON

2、MNMNMNBNB表2 ki的模糊規(guī)則表kieceNBNMNSZOPSPMPBNBNBNBNMNMNSZOZONMNBNBNMNSNSZOZONSNBNMNSNSZOPSPSZONMNMNSZOPSPMPMPSMNNSZOPSPSPMPBPMZOZOPSPSPMPBPBPBZOZOPSPMPMPBPB表3 kd的模糊規(guī)則表kdeceNBNMNSZOPSPMPBNBPSNSNBNBNBNMPSNMPSNSNBNMNMNSZONSZONSNMNMNSNSZOZOZONSNSNSNSNSZOPSZOZOZOZOZOZOZOPMPBNSPSPSPSPSPBPBPBPMPMPSPSPSPBKp,ki,k

3、d的模糊控制規(guī)則表建立好以后，可根據(jù)以下方法進(jìn)行kp,ki,kd的自適應(yīng)校正。將系統(tǒng)誤差e和誤差變化ec變化范圍定義為模糊集上的論域，即e，ec = -3，-2，-1,0,1,2,3,其模糊子集為e，ec = NB,NM,NS,ZO,PS,PM,PB,子集中元素分別代表負(fù)大，負(fù)中，負(fù)小，零，正小，正中，正大。應(yīng)用模糊合成推理設(shè)計(jì)PID參數(shù)的整定算法。第k個(gè)采樣時(shí)間的整定為Kp(k)=kp0+kp(k)Ki(k)=ki0+ki(k)Kd(k)=kd0+kd(k)在線運(yùn)行過(guò)程中，控制系統(tǒng)通過(guò)對(duì)模糊邏輯規(guī)則的結(jié)果處理、查表和運(yùn)算，完成對(duì)PID參數(shù)的在線自校正。其工作流程圖如下圖所示。入口e(k),e

4、c(k)模糊化e(k-1)=e(k)PID控制器輸出計(jì)算當(dāng)前kp,ki,kd模糊整定kp,ki,kdec(k)=e(k)-e(k-1)e(k)=r(k)-y(k)取當(dāng)前采樣值返回圖1 誤差的隸屬函數(shù)圖2 誤差變化率的隸屬函數(shù)圖3 kp的隸屬函數(shù)圖4 ki的隸屬函數(shù)圖5 kd的隸屬函數(shù)圖6 模糊系統(tǒng)fuzzpid.fis的結(jié)構(gòu)圖7 模糊推理系統(tǒng)的動(dòng)態(tài)仿真環(huán)境在程序PID_b.m中，利用所設(shè)計(jì)的模糊系統(tǒng)fuzzpid.fis進(jìn)行PID控制參數(shù)的整定，并利用模糊PID控制進(jìn)行階躍響應(yīng)，在第300個(gè)采樣時(shí)間時(shí)控制器輸出端加上1.0的干擾，響應(yīng)結(jié)果及PID控制參數(shù)的自適應(yīng)變化如圖8到13所示。圖8 模糊

5、PID控制階躍響應(yīng)圖9 模糊PID控制誤差響應(yīng)圖10 控制器輸入u圖11 kp的自適應(yīng)調(diào)整圖12 ki的自適應(yīng)調(diào)整圖13 kd的自適應(yīng)調(diào)整在對(duì)三階線性系統(tǒng)的控制中，利用穩(wěn)定邊界法進(jìn)行參數(shù)整定的經(jīng)典PID控制的超調(diào)量比模糊PID控制的超調(diào)量要大，但模糊PID控制存在一定的穩(wěn)態(tài)誤差。模糊控制用模糊集合和模糊概念描述過(guò)程系統(tǒng)的動(dòng)態(tài)特性，根據(jù)模糊集和模糊邏輯來(lái)做出控制決策，它在解決復(fù)雜控制問(wèn)題方面有很大的潛力，可以動(dòng)態(tài)地適應(yīng)外界環(huán)境的變化。附錄1 模糊系統(tǒng)設(shè)計(jì)程序PID_a%Fuzzy Turnning PID Controlclear all;close all;a=newfis('fuzz

6、pid');a=addvar(a,'input','e',-3,3); 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,-1,0);a=addmf(a,'input',1,'Z','trimf

7、',-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);a=addmf(a,'input',2,'NB','zmf&#

8、39;,-3,-1);a=addmf(a,'input',2,'NM','trimf',-3,-2,0);a=addmf(a,'input',2,'NS','trimf',-3,-1,0);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,

9、'PM','trimf',0,2,3);a=addmf(a,'input',2,'PB','smf',1,3);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,'

10、output',1,'NS','trimf',-0.3,-0.1,0);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,'

11、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

12、);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,

13、9;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,-1,0);a=addmf(a,'output',3,'Z','trimf',-2,0,2);a=add

14、mf(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 3 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

15、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 4 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

16、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,ru

17、lelist);a = setfis(a,'DefuzzMethod','centroid');writefis(a,'fuzzpid');a = readfis('fuzzpid');figure(1);plotmf(a,'input',1);figure(2);plotmf(a,'input',2);figure(3);plotmf(a,'output',1);figure(4);plotmf(a,'output',2);figure(5);plotmf(a,&#

18、39;output',3);figure(6);plotfis(a);fuzzy fuzzpid;showrule(a);ruleview fuzzpid;附錄2 模糊控制程序PID_b%Fuzzy PID Controlclose all;clear all;a=readfis('fuzzpid');ts=0.001;sys=tf(4.23,1,1.64,8.46);days=c2d(sys,ts,'tustin');num,den=tfdata(days,'v');u_1=0.0;u_2=0.0;u_3=0.0;y_1=0;y_2=0

19、;y_3=0;x=0,0,0'e_1=0;ec_1=0;kp0=0.40;kd0=1.0;ki0=0.0;for k=1:1:3000;time(k)=k*ts;r(k)=1.0;%Using fuzzy inference to tuning 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 0.3s) u(k)=u(k)+1.0;endy(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;e(k)=r(k)-y(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_