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M-file Matlab Function for Fuzzy System 

Diagram block of fuzzy control systems that will simulate a PD-like fuzzy control structure is shown in Figure 1, the fuzzy system has two inputs proportional and derivative, with the Gp is the proportional gain, Gd is the gain of the derivative and Go is a gain of the output.

Figure 1. Block Diagram for PD-like Fuzzy Controller

The simulation begins by setting the value of the initial conditions of the plant, and controller errors. Then step into the program looping process that took place during the time that we want (by considering the sampling time). Every time entering the iteration k, error (k) is calculated using Equation 1. Then the changing value of error (derivative error) is calculated by equation 2. After the error values and error change obtained, then the value is inserted into the fuzzy logic system so that the output obtained that will be used as plant input . With this plant input, then the plant output can be calculated. Next to the next iteration. This process can be seen in Figure 2:

          (1)

        (2)

Figure 2. Flowchart of Fuzzy Control Sistem Simulation

to simulate this system, we can download the functions first

1. Left membership (setiga_kr.rar)

2. Center membership (setiga_tg.rar)

3. Right membership (setiga_kn.rar)

4. Fuzzy controller (fuzz_satelit.rar)

5. Satelit plant (f_satelit.rar)

save them to work folder at matlab, and then write the script below
 

clear;

x1(1)=0;

x2(1)=0;

y(1)=0;

dt=0.01;

u(1)=1;

r=0.5

e(1)=-r;

gp=1;

gd=1;

go=1;

for n=1:1000

   k=n+1;

   e(k)=r-y(k-1);

   de(k)=100*(e(k)-e(k-1));

   u(k)=go*fuzz_satelit(gp*e(k),gd*de(k));

   %u(k)=e(k);

   [x1(k),x2(k)]=f_satelit(dt,u(k-1),x1(k-1),x2(k-1));

   y(k)=x1(k);

end

t=linspace(0,10,1001);

figure;

plot(t,y);

xlabel('detik');

ylabel('rad');

after then, execute the script that resulting the figure below

we can change the value of Gp, Gd and Go for the best result.

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