PID controller and PID tuner for a SIMO system
26 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
Hello,
I've been trying to search how to tune my PID using pidTuner and pidtune but I dont know how should I do it since my system has 1 input and 2 outputs. Because of this, I can´t use pidTuner as it seems that only works for SISO plants or 2 DOF PID controllers. Another thing to say is, that, this is my first control script in matlab, so I´m sure that there is a better way to create the system itself or the PID. Any help is highly appreciated!
So far, I managed to create the control scheme, but I need help for tunning the PID.
%% INIT
clear variables;
close all;
clc;
%% Reference input
% time
time=150;
%SINUSOIDAL
t = (0:0.1:time);
A=4;
w=0.8;
u1=A*sin(w*t);
%dr=zeros(1,length(r)-1);
%dr(1,:)=diff(r)./diff(t);
du1=gradient(u1,t);
%STEP
u2=step(tf(1,1,'InputDelay',10),t);
du2=gradient(u2,t);
%% variable initialization
[a,b,Kp,Kd,Ki,deltaT]= initVar();
%define space state system
f2 = @(t,X) [X(2); a*X(1)+b*X(2)];
%% DEFINE SYSTEM
% x1'= x2;
% x2'= a*x1+b*x2+u
As=[0 1;a b];
Bs=[0;1];
Cs=[1 0;0 1];
Ds=[0;0];
sys = ss(As,Bs,Cs,Ds);
systf=tf(sys);
%% PID
FC=pid(Kp,Ki,Kd,deltaT);
%% LOOP
% close the loop with the PID controller
size(systf*FC)
feedin=1;
feedout=1;
csys = feedback(systf*FC,feedin,feedout,1);
%output
ys= lsim(csys,u2,t);
rf=ys(:,1);
drf=ys(:,2);
max(rf)
max(drf)
%% PLOT
% plot position and speed of the system
figure
subplot(2,1,1)
plot(t,rf,'k', 'LineWidth',2)
hold on
plot(t,u2,'r', 'LineWidth',2)
xlabel('time(s)','fontweight','bold','FontSize',12)
ylabel('position','fontweight','bold','FontSize',12)
title('function evolution')
subplot(2,1,2)
plot(t,drf,'k', 'LineWidth',2)
hold on
plot(t,du2,'r', 'LineWidth',2)
xlabel('time(s)','fontweight','bold','FontSize',12)
ylabel('speed','fontweight','bold','FontSize',12)
%plot surface generated by the function
% [x1,x2] = meshgrid(-5:5);
% surff=a*x1+b*x2;
% figure
% surf(x1,x2,surff)
% view(135,45)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% FUNCTION
function [a,b,Kp,Kd,Ki,deltaT]= initVar()
%coefs
a=-0.3;
b=-1.1;
%gains
Kp=3;
Kd=0.8;
Ki=0.9;
deltaT=1e-1;
end
0 commentaires
Réponse acceptée
Sam Chak
le 24 Juil 2022
Modifié(e) : Sam Chak
le 24 Juil 2022
Hi @Mikel
Your system is
.
If you algebraically design u as
,
then the closed-loop becomes
.
Since you didn't specify the performance requirements, here is just a little test on the theoretical calculation. This method assumes that you can measure the velocity directly.
% parameters
a = -0.3;
b = -1.1;
% system
As = [0 1; a b];
Bs = [0; 1];
Cs = [1 0; 0 1];
Ds = [0; 0];
sys = ss(As, Bs, Cs, Ds);
Gp = tf(sys)
% gains designed by a simple algebra manipulation
Kp = 0.7;
Ki = 0.0;
Kd = 0.9;
Tf = 0.1;
Gc = pid(Kp, Ki, Kd, Tf)
% closed-loop
Gcl = feedback(Gc*Gp(1), 1)
% step(Gcl, 10) % can see the effect of zero that causes the overshoot
% Add a prefilter at the Reference Input to cancel out the zero (numerator of Gcl)
Gf = tf(10, [9.7 7])
% closed-loop with prefilter
Gclf = minreal(series(Gf, Gcl))
% system response
[y, t] = step(Gclf, 10);
plot(t, y), grid on
% PID output (I think so)
Gu = feedback(Gc, Gp(1));
Gfu = minreal(series(Gf, Gu))
step(Gfu, 10), grid on
Note: The following Block diagram in Simulink should produce the same outputs as demonstrated in MATLAB:
2 commentaires
Plus de réponses (0)
Voir également
Catégories
En savoir plus sur Classical Control Design dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!