模糊控制-模糊自适应整定PID控制仿真实验

1、实验三模糊自适应整定PID控制仿真实验一、实验目的1通过实验了解数字PID控制的原理2. 通过实验实现离散系统的数字PID控制仿真3通过实验了解模糊自适应整定PID控制的原理4. 通过实验实现模糊自适应整定PID控制仿真5. 通过实验进一步熟悉并掌握Matlab软件的使用方法二、实验内容1. 针对给定离散系统的输入信号的位置响应，设计离散PID控制器，编制相应的仿真程序。2若采样时间为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，编制该模糊自适应整定PID系统的Matlab仿真程序三、实验步骤1. 针对给定离散系统的阶跃信号、正弦信号和方波信号的位

2、置响应，设计离散PID控制器,编制相应的仿真程序。2. 确定模糊自整定 PID的算法基础3. 针对kp, ki , kd三个参数分别建立合适的模糊规则表4. 画出PID参数的在线自校正工作程序流程图5. 编制该模糊自适应整定PID系统的Matlab仿真程序四、实验要求1设被控对象为：采样时间为1ms,采用Z变换进行离散化，经过Z变换后的离散化对象为：yout(k)=-de n( 2)yout(k-1)-de n( 3)yout(k-2)-de n(4) yout(k-3)+num(2)u(k-1)+nu m(3)u(k-2)+nu m(4)u(k-3)针对离散系统的阶跃信号、正弦信号和方波信号

3、的位置响应，设计离散PID控制器。其中，S为信号选择变量，S=1时为阶跃跟踪，S=2时为方波跟踪，S=3时为正弦跟踪。2. 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，编制炉温模糊控制系统的Matlab仿真程序五、自适应模糊控制的规则1、控制规则:kl的整定的模糊控制表2.模糊控制器设计确定为双输入，三输出结构Membership Function Edrtor: UntitledFile Edit ViewFIS VanablesEl®色 outputlCurrent VariableTypeinputRange-11Disp

4、lay RangemiCfianglng parameter tor MF 3 to |1 J3 1确定每个变量的论域，其中每个变量都有一个模糊子集来表示。这个模糊子集中有 3个模糊子集，分别是：N, Z, P在编辑界面中，确定好每一个语言变量 的范围，以及隶属函数的类型。Membership Function Editor:ntitledFile Edit ViewFIS Vanablese . 2kdoutput vamable PtTChairtging parameter for MF 3 to (1 5如下图所示:输入模糊控制规则:Rule Editor: UntitledFile

5、Edit VieAr options1. it (& is N) and (ec is N) then (kp is NXki is l*O(kd is M) (1)2. If (e is N) and (ecisZ) then (kp is ZXki is NXkd is N)3. If (els N) and (ec is ZJthen (kp Is Z)0d Is 石(kd Is 4. If (e is N) end (ec is Z) then (kp is ZXki is ZMM is Z) 1)5. If (B is Z) andec is Z) then (kp is Z

6、Xki is Z)(kd is Z)G lf(0isZ) and (ec Is P) then (kp Is Z)0tl is XffmA is 7 K (e is I) and (ec is P)theri (kp Is 罚i IsisZ) (1)a. If (e is Z) and (ec is P) then (kp is 司(ki is PXkd is P) (1) 9 If (e is P) and (ec is Z) then (kp Is SXki is P)(kd Is P) (1) 10. nf (e Is P) and (ec Is N) then 脚 is S)(ki i

7、s P)(kd11 If (e is P) and (ec is N) tfien (kp is ZXki is P)(kd is P) (1) 3ande isand ec isJKienkpisandId Isnonienonenotnotl Ccrmectloti .训tight:notNp noneDeist冬 rulenotnotAdd rule Change ruleThe rule is added六、仿真结果PID控制器Kp参数在控制过程中的变化曲线:Q ScopeTime offset： 0Ki参数:Kd参数:Q Scope2 旨 0 炉 p AESIS S A0 11S11

8、790.1 IBI 1179IQ 2030405060708090100Time offsd: 0七、实验程序(一)%Fuzzy Tunning PID Control Clear all;Close all;a=n ewfis('fuzzpid');a=addvar(a,' in put','e',-1 1);a=addmf(a,' in put','1','N','zmf,-1,-1/3);a=addmf(a,' in put','1','Z

9、9;,'trimf,-2/3,0,2/3);a=addmf(a,' in put','1','P','smf,1/3,1);a=addvar(a,' in put','ec',-1 1); a=addmf(a,'i nput','2','N','zmf,-1,-1/3); a=addmf(a,' in put','2','Z','trimf,-2/3,0,2/3); a=addmf(a,&

10、#39; in put','2','P','smf,1/3,1);a=addvar(a,'output','kp',-10 10); a=addmf(a,' in put','1','N','zmf,-10,-3);a=addmf(a,' in put','1','Z','trimf,-5,0,5); a=addmf(a,' in put','1','P',

11、'smf,3,10);a=addvar(a,'output','ki',-3 3); a=addmf(a,'output','2','N','zmf,-3,-1);a=addmf(a,'output','2','Z','trimf,-2,0,2); a=addmf(a,'output','2','P','smf,1,3);a=addvar(a,'output','k

12、d',-5 5); a=addmf(a,'output','3','N','zmf,-5,-1);a=addmf(a,'output','3','Z','trimf,-3,0,3); a=addmf(a,'output','3','P','smf,1,5);Rulelist=1 1 1 1 1 1 1;1 2 1 2 1 1 1;1 2 2 1 2 1 1;1 3 1 2 1 1 1;1 3 2 3 2 1 1;2 1

13、1 1 1 1 1;2 2 3 3 1 1 1;2 1 2 2 3 1 1;2 3 2 1 3 1 1;2 2 3 1 2 1 1;3 1 2 1 1 1 1;3 2 3 1 2 1 1;3 1 2 1 2 1 1;3 3 1 2 3 1 1;3 2 3 1 2 1 1; a=addrule(a,rulelist); a=setfis(a,'DefuzzMethod','ce ntroid'); writefis(a,'fuzzy');a=readfis('fuzzpid');figure(1);Plotmf(a,' in

14、 put',1);figure(2);Plotmf(a,' in put',2);figure(3);Plotmf(a,'output',1);figure(4);Plotmf(a,'output',2);figure(5);Plotmf(a,'output',3);figure(6);Plotfis(a);fuzzy fuzzpid;showrule(a);ruleview fuzzpid;(二)%Fuzzy PID Con trolClear all;Close all;Warni ng off;a=readfis(&

15、#39;fuzzpid');t=0.001;sys=tf(122,1,26,0); dsys=c2d(sys,ts,'z');nu m,de n=tfdata(dsys,'v');u-仁 0;u-2=0;y-1=0;y=2=0;e-1=0;ec-仁 0;ei=0;ed=0;kp0=0;ki0=0;kd0=0;for k=1:1:1000Time(k)=k*ts;r(k)=1;%Us ing fuzzy inference to tunning PID k-pid=evalfis(e-1,ec_1,a);kp(k)=kp_0+k_pid(1); ki(k)

16、=ki_0+k_pid(2);kd(k)=kd_0+k_pid(3);u(k)=kp(k)*e_1+ki(k)*ei+kd(k)*ed;y(k)=-de n(2)*y_1-de n(3)*y_2+num( 2)*u_1+ num(3) *u_2;e(k)=r(k)-y(k);%Retur n of parameters% u_2=u_1;u_1u(k)=0;y_2=y_1;y_12=y (2)；ei=ei+e(k)*ts;ec(k)=e(k)-e_1;e_1=e(k);ec_1=ec(k);endfiure(1);plot(time,r,'r',time,y,'b:','li newidth',2);xlabel(time(s)');ylabel('r,y');lege nd('ldeal ositi on ','Practical positi on');fiure(2);subplot(211);plot(time,kp,'r','li newidth',