基本PID控制.rar_PID控制_SIMULINK_控制系统MATLAB

%PID Controller with Partial differential 偏微分PID控制器 clear all; close all; ts=0.001;%采样时间 sys=tf(5.235e005,[1,87.35,1.047e004,0]);%被控对象为三阶传递函数 dsys=c2d(sys,ts,'z'); %把上面的连续时间传递函数转换为离散模型 [num,den]=tfdata(dsys,'v');%该离散模型的分子分母多项式系数 u_1=0;u_2=0;u_3=0;u_4=0;u_5=0;%初始化值 y_1=0;y_2=0;y_3=0; yn_1=0; error_1=0;error_2=0;ei=0; kp=0.20;ki=0.05;%PID比例系数 sys1=tf([1],[0.04,1]); %Low Freq Signal Filter， dsys1=c2d(sys1,ts,'tustin'); %转换离散模型时。。。。 [num1,den1]=tfdata(dsys1,'v');%该离散模型的分子分母多项式系数 f_1=0; %初始化 M=3; for k=1:1:1000 %步进，for循环，循环一次给time和r变量矩阵赋值 time(k)=k*ts; %每次循环赋值 yd(k)=20; %Step Signal 阶跃信号 %Linear model y(k)=-den(2)*y_1-den(3)*y_2-den(4)*y_3+num(2)*u_1+num(3)*u_2+num(4)*u_3; %这个函数真的没看懂 if M==1 %No noisy signal error(k)=yd(k)-y(k); %误差 filty(k)=y(k); end n(k)=5.0*rands(1); %Noisy signal yn(k)=y(k)+n(k); if M==2 %No filter filty(k)=yn(k); error(k)=yd(k)-filty(k); end if M==3 %Using low frequency filter filty(k)=-den1(2)*f_1+num1(1)*(yn(k)+yn_1); error(k)=yd(k)-filty(k); end %I separation if abs(error(k))<=0.8 ei=ei+error(k)*ts; else ei=0; end u(k)=kp*error(k)+ki*ei; %----------Return of PID parameters------------ yd_1=yd(k); 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=y(k); f_1=filty(k); yn_1=yn(k); error_2=error_1; error_1=error(k); end figure(1); subplot(211); plot(time,yd,'r',time,filty,'k:','linewidth',2); xlabel('time(s)');ylabel('yd,y'); legend('Ideal position signal','Position tracking'); subplot(212); plot(time,u,'r','linewidth',2); xlabel('time(s)');ylabel('u'); figure(2); plot(time,n,'r','linewidth',2); xlabel('time(s)');ylabel('Noisy signal');