利用MATLAB提供的模糊逻辑工具箱函数进行仿真实验.ppt

clearall;closeall;ts=20;sys1=tf(1,60,1,inputdelay,80);%生成或转换传递函数模型dsys1=c2d(sys1,ts,zoh);%将连续系统离散化num1,den1=tfdata(dsys1,v);%获得传递函数模型数据,例,系统被控对象为：,利用MATLAB提供的模糊逻辑工具箱函数进行仿真实验,%传统PID算法u_1=0;u_2=0;u_3=0;u_4=0;u_5=0;y_1=0;y_2=0;y_3=0;error_1=0;ei=0;fork=1:1:300time(k)=k*ts;rin(k)=40;yout(k)=-den1(2)*y_1+num1(2)*u_5;error(k)=rin(k)-yout(k);ei=ei+error(k)*ts;,kp=0.8;ki=0.005;kd=3.0;u(k)=kp*error(k)+kd*(error(k)-error_1)/ts+ki*ei;,ifu(k)=110u(k)=110;endifu(k)=-110u(k)=-110;end%返回PID参数u_5=u_4;u_4=u_3;u_3=u_2;u_2=u_1;u_1=u(k);y_3=y_2;y_2=y_1;y_1=yout(k);error_1=error(k);end,%模糊PID控制系统a=newfis(fuzzf);%创建新的模糊推理系统添加语言变量、隶属度函数（略）f1=1;f2=1;f3=1.5；Error=rin-Yout;,sys1=tf(1,60,1,inputdelay,80);dsys=c2d(sys1,ts,zoh);num,den=tfdata(dsys,v);U_1=0;U_2=0;U_3=0;U_4=0;U_5=0;Y_1=0;Y_2=0;Y_3=0;e_1=0.0;ec_1=0.0;Error_1=0;Ei=0fork=1:1:300time(k)=k*ts;rin(k)=40;U(k)=evalfis(e_1,ec_1,a2);%完成模糊推理计算,Yout(k)=-den(2)*Y_1+num(2)*U_5;Error(k)=rin(k)-Yout(k);ki=0.003;Ei=Ei+Error(k)*ts;U(k)=U(k)+ki*Ei;%返回参数U_5=U_4;U_4=U_3;U_3=U_2;U_2=U_1;U_1=U(k);Y_3=Y_2;Y_2=Y_1;Y_1=Yout(k);e_1=Error(k);ec_1=Error(k)-Error_1;Error_1=Error(k);end,figure(1);plot(time,rin,b,time,yout,r);xlabel(time(s);ylabel(rin,yout);figure(2);plot(time,u,r);xlabel(time(s);ylabel(u);figure(3);plot(time,rin,b,time,Yout,r);xlabel(time(s);ylabel(rin,yout);figure(4);plot(time,U,r);xlabel(time(s);ylabel(u);figure(5);plotfis(a2);figure(6);plotmf(a2,input,1);figure(7);plotmf(a2,input,2);figure(8);plotm