.. | ||
assign_6_pso_with_timestamp.ipynb | ||
assign_6_pso.ipynb | ||
assign_6_pso.m | ||
Presentasi Sistem Kendali Pre-UTS.pptx | ||
README.md | ||
tugas6_ZN1.m |
Improved Particle Swarm Optimization and Ziegler-Nicols 1 on PID Tuning
This dir is belong to Control System class contains with Tuning PID with ZN1 and IPSO on motor system.
Software
This program ran in Matlab
IPSO Method
Variables
s = tf('s');
defines s
as 'frequency domain' for transfer function and will be used further.
J = 0.01;
b = 0.1;
K = 0.01;
R = 1;
L = 0.5;
Those variable comes from BLDC control system.
c1=2; c2=2; w_max = 1; w_min = 0.1; particles=50; iterations=100;
var=3; e_max = 1; e_min=0.1;
% Search limit
lim_min = 0;
lim_max = 2500;
Variable above is the constant for PSO tuning.
Testing
ITAE Cost Function
Step Response
Ramp Response
Impulse Response
Acceleration Response
Results
Elapsed time is 18.701024 seconds.
Before PSO-PID
RiseTime: 1.0161
SettlingTime: 1.8471
SettlingMin: 0.0819
SettlingMax: 0.0907
Overshoot: 0
Undershoot: 0
Peak: 0.0907
PeakTime: 3.0168
SSError: 0.9095
After PSO-PID
Kp = 853.3161
Ki = 74.1078
Kd = 2.4810e+03
RiseTime: 9.5287e-04
SettlingTime: 0.0012
SettlingMin: 0.9949
SettlingMax: 0.9976
Overshoot: 0
Undershoot: 0
Peak: 0.9976
PeakTime: 0.0036
SSError: 0.0024
DelayTime: 0.000595
ZN1 Method
Variables
s = tf('s');
defines s
as 'frequency domain' for transfer function and will be used further.
J = 0.01;
b = 0.1;
K = 0.01;
R = 1;
L = 0.5;
Those variable comes from BLDC control system.
tic
timeVal=tic;
[y,t] = step(motor);
h = mean(diff(t));
dy = gradient(y, h); % Numerical Derivative
[~,idx] = max(dy); % Index Of Maximum
b = [t([idx-1,idx+1]) ones(2,1)] \ y([idx-1,idx+1]); % Regression Line Around Maximum Derivative
tv = [-b(2)/b(1); (1-b(2))/b(1)]; % Independent Variable Range For Tangent Line Plot
f = [tv ones(2,1)] * b; % Calculate Tangent Line
L = tv(1);
T = tv(2);
figure(1)
plot(t, y)
hold on
plot(tv, f, '-r') % Tangent Line
plot(t(idx), y(idx), '.r')
title('Mencari tangent line plant ')% Maximum Vertical
hold off
grid
Process above is to find tangent line and L and T constant
After L and T constant is obtained, the values is used to obtained Kp, Ki, and Kd constant
control = tf(zeros(1,1,5));
sys=tf(zeros(1,1,5));
complete=tf(zeros(1,1,5));
% sistem dengan P
kp = T/L
control(:,:,1)= tf([0 kp 0],[1 0]);
% sistem dengan PI
kp = 0.9*T/L
Ti= L/0.3;
ki = kp/Ti
control(:,:,2)= tf([0 kp ki],[1 0]);
% sistem dengan PID
kp = 1.2*T/L
Ti= 2*L;
ki = kp/Ti
Td = 0.5*L;
kd = kp*Td
control(:,:,3)= tf([kd kp ki],[1 0]);
Testing
Step Response
Ramp Response
Impulse Response
Acceleration Response
Results
Elapsed time is 0.065802 - 0.455767 seconds.
Before ZN1-PID
RiseTime: 1.0161
SettlingTime: 1.8471
SettlingMin: 0.0819
SettlingMax: 0.0907
Overshoot: 0
Undershoot: 0
Peak: 0.0907
PeakTime: 3.0168
SSError: 0.9095
After ZN1-PID
Control P: Kp = 140.9417 Control PI: Kp = 126.8475 ; Ki = 711.9513 Control PID: Kp = 169.13; Ki = 1.5821e+03; Kd = 4.5201
RiseTime: 0.0676
SettlingTime: 0.8486
SettlingMin: 0.8129
SettlingMax: 1.4349
Overshoot: 43.4944
Undershoot: 0
Peak: 1.4349
PeakTime: 0.17391
SSError: -0.0021
DelayTime: 0.0444
Notes
Contact nanda.r.d@mail.ugm.ac.id for more information
Links
You can access the source code here github.com/nandard/control-system.git