模糊pid仿真

				%Fuzzy PID Control
				close all;
				clear all;
				
				a=readfis('fuzzpid');   %Load fuzzpid.fis
				
				ts=0.001;
				sys=tf(5.235e005,[1,87.35,1.047e004,0]);
				dsys=c2d(sys,ts,'tustin');
				[num,den]=tfdata(dsys,'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;
				
				for k=1:1:3000
				time(k)=k*ts;
				
				r(k)=sign(sin(2*pi*k*ts));
				%Using fuzzy inference to tunning PID
				k_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;
				end
				
				y(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_1=y(k);
				   
				   x(1)=e(k);            % Calculating P
				   x(2)=e(k)-e_1;        % Calculating D
				   x(3)=x(3)+e(k)*ts;    % Calculating I
				
				   ec_1=x(2);
				   e_2=e_1;
				   e_1=e(k);
				end
				
				figure(1);
				plot(time,r,'b',time,y,'r');
				xlabel('time(s)');ylabel('rin,yout');
				figure(2);
				plot(time,e,'r');
				xlabel('time(s)');ylabel('error');
				figure(3);
				plot(time,u,'r');
				xlabel('time(s)');ylabel('u');
				figure(4);
				plot(time,kp,'r');
				xlabel('time(s)');ylabel('kp');
				figure(5);
				plot(time,ki,'r');
				xlabel('time(s)');ylabel('ki');
				figure(6);
				plot(time,kd,'r');
				xlabel('time(s)');ylabel('kd');