模糊控制PID設(shè)計大作業(yè)-

1、參考教材中例子設(shè)計一包含了模糊技術(shù)與PID技術(shù)的混合智能控制器，其被控對象為：Gp(s)=4.232(s21.64s8.46)采樣時間為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。要求詳細描述控制系統(tǒng)的設(shè)計，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)計及其采用的模糊規(guī)則，分析仿真結(jié)果并進行總結(jié)。表1kp的模糊規(guī)則表NBNMNSZOPSPMPBNBPBPBPMPMPSZOZONMPBPBPMPSPSZONSNSPMPMPMPSZONSNSZOPMPMPSZONSNMNMPSPSPSZONSNSNMNMPMPSZONSNMNMNMNBPB

2、ZOZONMNMNMNBNB表2ki的模糊規(guī)則表2iecNBNMNSZOPSPMPBNBNBNBNMNMNSZOZONMNBNBNMNSNSZOZONSNBNMNSNSZOPSPSZONMNMNSZOPSPMPMPSMNNSZOPSPSPMPBPMZOZOPSPSPMPBPBPBZOZOPSPMPMPBPB表3kd的模糊規(guī)則表&decNBNMNSZOPSPMPBNBPSNSNBNBNBNMPSNMPSNSNBNMNMNSZONSZONSNMNMNSNSZOZOZONSNSNSNSNSZOPSZOZOZOZOZOZOZOPMPBNSPSPSPSPSPBPBPBPMPMPSPSPSPBKp

3、,ki,kd的模糊控制規(guī)則表建立好以后，可根據(jù)以下方法進行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,P用集中元素分別代表負大，負中，負小，零，正小，正中，正大。應(yīng)用模糊合成推理設(shè)計PID參數(shù)的整定算法。第k個采樣時間的整定為Kp(k)=kp0+Akp(k)Ki(k)=ki0+Aki(k)Kd(k)=kd0+Akd(k)在線運行過程中，控制系統(tǒng)通過對模糊邏輯規(guī)則的結(jié)果處理、查表和運算，完成對PID參數(shù)的在線自校正。其工作流程圖如下圖所示。入口FileE

4、ditViewInsertToolsDesktopWindowHelpFileEditViewInsertToolsDesktopWindowHelpn日n全心w白要/國I口圖2誤差變化率的隸屬函數(shù)0目S3JFileEditViewInsertTooIsDesktopWindowHelp，dw9E，E口皂苦FileEdHViewInsertToolsDesktopWindowHelp圖4ki的隸屬函數(shù)FileEditViewInsertToolsDesktopWindowHelpRu®Viewer；fuzzpid圖6模糊系統(tǒng)fuzzpid.fis的結(jié)構(gòu)TltdlE口|回S3ViewO

5、ptionskp=-0.04ki=0.00799kd=-D.G05ec=0圖7模糊推理系統(tǒng)的動態(tài)仿真環(huán)境在程序PIDb.m中，利用所設(shè)計的模糊系統(tǒng)fuzzpid.fis進行PID控制參數(shù)的整定，并利用模糊PID控制進行階躍響應(yīng)，在第300個采樣時間時控制器輸出端加上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?；谾igure1圖8模*®PID控制階躍響應(yīng)S3S3Figure31=1：±±|FfleEditViewInsertTeoliDesktopWindowHelp口占si©I住|r或*園要/”|niEiiia1n11B11111

6、1-1000.511.522.53time(sj圖10控制器輸入uFileEditViewInsertToolsDesktopWindowHelp0口d*11用1口0050.04003002。-01j立00.01- 002- 003- 0.04- 0.0500.511.522.53time(s)圖12ki的自適應(yīng)調(diào)整QFigure6I1=1I回I費JFileEditViewInsertToolsDesktopWindowHelp曰七合。©|4|戈2丹夏口國！0t|3-2.5-2i'O1.5-1 r-0.5-ol1111100,511.522.63time(s)圖13kd的自適

7、應(yīng)調(diào)整在對三階線性系統(tǒng)的控制中，利用穩(wěn)定邊界法進行參數(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程系統(tǒng)的動態(tài)特性，根據(jù)模糊集和模糊邏輯來做出控制決策，它在解決復(fù)雜控制問題方面有很大的潛力，可以動態(tài)地適應(yīng)外界環(huán)境的變化。附錄1模糊系統(tǒng)設(shè)計程序PID_a%FuzzyTurnningPIDControlclearall;closeall;a=newfis('fuzzpid');a=addvar(a,'input','e',-3,3);a=addmf(a,'in

8、put',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',-2,0,2);a=addmf(a,'input',1,'PS','trimf',-1

9、,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',-3,-1);a=addmf(a,'input',2,'NM','trimf',-3,-2

10、,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,'PM','trimf',0,2,3);a=addmf(a,'input',2,'PB&#

11、39;,'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,'output',1,'NS','trimf',-0.3,-0.1,0);a=addmf(a,'ou

12、tput',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',-

13、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);

14、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'

15、;,'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=addmf(a,'output',3,'PS','trimf',-1,1,3);a=addmf(a,&#

16、39;output',3,'PM','trimf',0,2,3);a=addmf(a,'output',3,'PB','smf',1,3);rulelist=1171511;1231311;1362111;1462111;1553111;1644211;1 744511;217151122713112362111245321111;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11;11

17、;11;11;11;11;a=addrule(a,rulelist);26443273443161432623336323453235443363533735441624426244353344443453534626347264515245253453444543545535456264572746154762445633556425565265662756717771447724467325674266752657617577177a=setfis(a,'DefuzzMethod','centroid');writefis(a,'fuzzpid

18、9;);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,'output',3);figure(6);plotfis(a);fuzzyfuzzpid;showrule(a);ruleviewfuzzpid;附錄2模糊控制程序PID

19、_b%FuzzyPIDControlcloseall;clearall;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;y_3=0;x=0,0,0'e_1=0;ec_1=0;kp0=0.40;kd0=1.0;ki0=0.0;fork=1:1:3000;time(k)=k*ts;r(k)=1.0;%Using

20、fuzzyinferencetotuningPIDk_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);ifk=300%addingdisturbance(1.0vattime0.3s)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);%ReturnofPIDparameters%u_3=u_2;u_2=