fuzzysugeno.m

先进PID控制matlab仿真（第二版） 1、所有仿真算法按章归类

%Sugeno type fuzzy control for single inverted pendulum 
close all; 

P=[-10-10i;-10+10i]; %Stable pole point 

F1=place(A1,B1,P) 
F2=place(A2,B2,P) 
F3=place(A3,B3,P) 
F4=place(A4,B4,P) 
F5=place(A5,B5,P) 


tc=newfis('tc','sugeno'); 
tc=addvar(tc,'input','theta',[-15,15]*pi/180); 
tc=addmf(tc,'input',1,'NG','gaussmf',[5,-15]*pi/180); 
tc=addmf(tc,'input',1,'ZR','gaussmf',[5,0]*pi/180); 
tc=addmf(tc,'input',1,'PO','gaussmf',[5,15]*pi/180); 

tc=addvar(tc,'input','omega',[-200,200]*pi/180); 
tc=addmf(tc,'input',2,'NG','gaussmf',[50,-200]*pi/180); 
tc=addmf(tc,'input',2,'ZR','gaussmf',[50,0]*pi/180); 
tc=addmf(tc,'input',2,'PO','gaussmf',[50,200]*pi/180); 

tc=addvar(tc,'output','u',[-300,0]); 
tc=addmf(tc,'output',1,'No.1','linear',[F1(1),F1(2)]); 
tc=addmf(tc,'output',1,'No.2','linear',[F2(1),F2(2)]); 
tc=addmf(tc,'output',1,'No.3','linear',[F3(1),F3(2)]); 
tc=addmf(tc,'output',1,'No.4','linear',[F4(1),F4(2)]); 
tc=addmf(tc,'output',1,'No.5','linear',[F5(1),F5(2)]); 

rulelist=[1 1 4 1 1; 
1 2 3 1 1; 
1 3 5 1 1; 
2 1 2 1 1; 
2 2 1 1 1; 
3 1 5 1 1; 
3 2 3 1 1; 
3 3 4 1 1]; 
tc=addrule(tc,rulelist); 


model=newfis('model','sugeno'); 
model=addvar(model,'input','theta',[-15,15]*pi/180); 
model=addmf(model,'input',1,'NG','gaussmf',[5,-15]*pi/180); 
model=addmf(model,'input',1,'ZR','gaussmf',[5,0]*pi/180); 
model=addmf(model,'input',1,'PO','gaussmf',[5,15]*pi/180); 

model=addvar(model,'input','omega',[-200,200]*pi/180); 
model=addmf(model,'input',2,'NG','gaussmf',[50,-200]*pi/180); 
model=addmf(model,'input',2,'ZR','gaussmf',[50,0]*pi/180); 
model=addmf(model,'input',2,'PO','gaussmf',[50,200]*pi/180); 

model=addvar(model,'input','u',[-5,5]); 
model=addmf(model,'input',3,'Any','gaussmf',[1.5,-5]); 

model=addvar(model,'output','d_theta',[-200,200]*pi/180); 
model=addmf(model,'output',1,'No.1','linear',[0 1 0 0]); 
model=addmf(model,'output',1,'No.2','linear',[0 1 0 0]); 
model=addmf(model,'output',1,'No.3','linear',[0 1 0 0]); 
model=addmf(model,'output',1,'No.4','linear',[0 1 0 0]); 
model=addmf(model,'output',1,'No.5','linear',[0 1 0 0]); 

model=addvar(model,'output','d_omega',[-200,200]*pi/180); 
model=addmf(model,'output',2,'No.1','linear',[A1(2,1),0,B1(2),0]); 
model=addmf(model,'output',2,'No.2','linear',[A2(2,1),0,B2(2),0]); 
model=addmf(model,'output',2,'No.3','linear',[A3(2,1),0,B3(2),0]); 
model=addmf(model,'output',2,'No.4','linear',[A4(2,1),A4(2,2),B4(2),0]); 
model=addmf(model,'output',2,'No.5','linear',[A5(2,1),A5(2,2),B5(2),0]); 

rulelist1=[1 1 0 4 4 1 1; 
1 2 0 3 3 1 1; 
1 3 0 5 5 1 1; 
2 1 0 2 2 1 1; 
2 2 0 1 1 1 1; 
2 3 0 2 2 1 1; 
3 1 0 5 5 1 1; 
3 2 0 3 3 1 1; 
3 3 0 4 4 1 1]; 
model=addrule(model,rulelist1); 

ts=0.020; 
x=[0.20;0]; %Initial state 

for k=1:1:100 
time(k)=k*ts; 
u(k)=(-1)*evalfis([x(1),x(2)],tc); %Using feedback control 

k0=evalfis([x(1),x(2),u(k)],model)'; %Using fuzzy T-S model 
x=x+ts*k0; 

y1(k)=x(1); 
y2(k)=x(2); 
end 
figure(1); 
subplot(211); 
plot(time,y1),grid on; 
xlabel('time(s)'),ylabel('Angle'); 
subplot(212); 
plot(time,y2),grid on; 
xlabel('time(s)'),ylabel('Angle rate'); 

figure(2); 
plot(time,u),grid on; 
xlabel('time(s)'),ylabel('controller output'); 

figure(3); 
plotmf(tc,'input',1); 
figure(4); 
plotmf(tc,'input',2); 

showrule(tc); 
showrule(model);