what should we do that fuzzypid track the reference trajectory .
a_p=0.24;
a_d=0.12;
a_i=0.22;
s=0.8*e12;
kp=80000000; ki=5000; kd=2000;
ks_p=0.5*(1/(a_p+abs(s)-a_p*abs(s))+(a_p-1)/(a_p*abs(s)-1));
ks_d=0.5*(1/(a_d+abs(s)-a_d*abs(s))+(a_d-1)/(a_d*abs(s)-1));
ks_i=0.5*(1/(a_i+abs(s)-a_i*abs(s))+(a_i-1)/(a_i*abs(s)-1));
phi_p=s*ks_p;
phi_d=s*ks_d;
phi_i=s*ks_i;
u=kp*phi_p+ki*phi_i+kd*phi_d;
find an attached graph
Hi Chandar Kumar
Researchers are encouraged to the promote academic research and the exchange of results and opinions in this forum. However, this can be regarded as a low-effort post. The title of your post "What should we do?" cannot be meaningfully interpreted without taking a wild guess.
On the code, I have absolutely no idea what they are without the standard math notations or technical comments. Furthermore, running the cluttered code shows errors of some undefined variables. In fact, no where in the code shows any intelligible direct relation to the standard inference system of a typical Fuzzy PID [controller].
Please consider editing the post and fix the code (to plot the attached figure) if you are looking for meaningful advices from other researchers.
Hi Chandar Kumar
What exactly is this function? Can you clarify what the function does? The plot shows it looks like a "ω" sign. Is it a novel fuzzy membership function that you created?
Hi Chandar Kumar
I attempt to run your code based on what makes sense to me. It is a nonlinear PID controller with fixed PID gains. However, your selected functions contain singularities outside the operating range {–4 < s < 4}, as shown in the 'ω' plot.
Also, the integral and derivative terms are incorrect because the integral gain Ki should multiply with the transfer element of integral of s, and the derivative gain Kd should multiply with the transfer element of derivative of s.
% ~~~~~~~~~~~~~~~~~~~~~~~~~
sp = linspace(-1, 1, 2001); % s is the error
si = linspace(-1, 1, 2001); % integral of s
sd = linspace(-1, 1, 2001); % derivative of s
kp = 80000000; % static P gain
ki = 5000; % static I gain
kd = 2000; % static D gain
a_p = 0.24;
a_i = 0.22;
a_d = 0.12;
ks_p = 0.5*(1./(a_p + abs(sp) - a_p*abs(sp)) + (a_p - 1)./(a_p*abs(sp) - 1));
ks_i = 0.5*(1./(a_i + abs(si) - a_i*abs(si)) + (a_i - 1)./(a_i*abs(si) - 1));
ks_d = 0.5*(1./(a_d + abs(sd) - a_d*abs(sd)) + (a_d - 1)./(a_d*abs(sd) - 1));
phi_p = sp.*ks_p;
phi_i = si.*ks_i;
phi_d = sd.*ks_d;
subplot(311)
plot(sp, phi_p, 'linewidth', 2, 'Color', [0.9250, 0, 0.8250])
subplot(312)
plot(si, phi_i, 'linewidth', 2, 'Color', [0.3010, 0.7450, 0.9330])
subplot(313)
plot(sd, phi_d, 'linewidth', 2, 'Color', [0.9290, 0.6940, 0.1250])
- Badges
- Science topic
- Similar topics
- Engineering
- Control Theory
- Control Systems
- Control Systems Engineering