From fc83b04f43ac0b05c06e500efa221c36af5d930b Mon Sep 17 00:00:00 2001 From: nandard Date: Wed, 21 Sep 2022 20:28:38 +0700 Subject: [PATCH] Add assignment five --- Assignment 5 - PD/README.md | 93 +++++++++++++++++++++++++++++++++++++ Assignment 5 - PD/week_5.m | 33 +++++++++++++ 2 files changed, 126 insertions(+) create mode 100644 Assignment 5 - PD/README.md create mode 100644 Assignment 5 - PD/week_5.m diff --git a/Assignment 5 - PD/README.md b/Assignment 5 - PD/README.md new file mode 100644 index 0000000..ee9c5ad --- /dev/null +++ b/Assignment 5 - PD/README.md @@ -0,0 +1,93 @@ +# Derivative Effect on Control System +This dir is belong to Control System class contains with Derivative Effect on Control System. This code 100% original made by my hand :), please leave some notes if you're going to use it. Thanks! + +## Software +This program ran in Matlab + +## 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. +``` +Kp = 1; +Kd = 1; +% Kd = 3; +% Kd = 5; +% Kd = 7; +% Kd = 9; +``` +Variable above is the constant from PD control, we're trying to varies the constant to analyze derivative effect on control system + +## Process +The BLDC motor control system should be defined as transfer function by initialize its numerator-denumerator and *tf()* function. +``` +num_motor = [K]; +den_motor = [J*L J*R+b*L R*b+K*K]; + +motor = tf(num_motor,den_motor) +``` +Besides the plant function, the PD-control system defined by `C = tf([Kd Kp 0],[0 1 0])`. The vector is set according to PD formula which `PD = Kp + Kd * s`. After that, both of system are multiplied each others without feedback by `complete = feedback(motor*C,1);` + +That system will be test with step, ramp, and impulse input by call below lines +``` +subplot(311), impulse(complete); % Impulse reponse +subplot(312), step(complete); % Step Response +subplot(313), step(complete / s); % Ramp response +stepinfo(complete) +``` + +Since Matlab doesn't provide any steady-state error calculation, we process it by call below lines +``` +[y,t] = step(complete); % Calculate Steady-State error +sse = abs(1 - y(end)) +``` +Last line works to limit the graph +``` +xlim([0 50]) +ylim([0 3]) +``` + + +## Testing +For Kp = 1 +| Param | Kd = 1 | Kd = 3 | Kd = 5 | Kd = 7 | Kd = 9 | +|--- |--- |--- |--- |--- |--- | +| Rise Time | 0.0540 | 0.0140 | 0.0081 | 0.0057 | 0.0044 | +| Settling Time | 2.1356 | 3.2085 | 3.9313 | 4.6494 | 5.3646 | +| Overshoot | 50.9930 | 232.5791 | 359.4791 | 452.0385 | 522.2002 | +| SSE | 0.9088 | 0.9077 | 0.9075 | 0.9075 | 0.9069 | + +### Kp = 1, Kd = 1 + +![Kp = 1, Kd = 1](https://user-images.githubusercontent.com/77116615/189711219-a3d00c73-0902-4a3f-899c-aca785cf0e6c.png) +### Kp = 1, Kd = 3 + +![Kp = 1, Kd = 3](https://user-images.githubusercontent.com/77116615/189711238-016657a1-8b3d-4209-8033-192464c00bed.png) +### Kp = 1, Kd = 5 + +![Kp = 1, Kd = 5](https://user-images.githubusercontent.com/77116615/189711244-acaa9905-21dc-4e80-915e-c628775a6665.png) +### Kp = 1, Kd = 7 + +![Kp = 1, Kd = 7](https://user-images.githubusercontent.com/77116615/189711248-cdac4205-6511-460d-8eb8-96378564774e.png) +### Kp = 1, Kd = 9 + +![Kp = 1, Kd = 9](https://user-images.githubusercontent.com/77116615/189711253-c2a2208c-fdb8-4640-b419-b2909250ed0e.png) + +## Conclusion +Based on previous tests, we conclude that by adding Integral constant : +* Risie time is **increased** +* Settling time is **increased** +* Overshoot is **decreased** +* SSE is **decreased** + +### 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](https://github.com/nandard/control-system.git) diff --git a/Assignment 5 - PD/week_5.m b/Assignment 5 - PD/week_5.m new file mode 100644 index 0000000..aacc209 --- /dev/null +++ b/Assignment 5 - PD/week_5.m @@ -0,0 +1,33 @@ +s = tf('s'); +J = 0.01; +b = 0.1; +K = 0.01; +R = 1; +L = 0.5; + +Kp = 1; +%Kd = 1; +%Kd = 3; +%Kd = 5; +%Kd = 7; +Kd = 9; + +num_motor = [K]; +den_motor = [J*L J*R+b*L R*b+K*K]; +motor = tf(num_motor,den_motor) + +C = tf([Kd Kp 0],[0 1 0]) + +complete = feedback(motor*C,1); + +subplot(311), impulse(complete); % Impulse reponse +subplot(312), step(complete) % Step Response +subplot(313), step(complete / s); % Ramp response +title("Ramp Response"); +stepinfo(complete) + +[y,t] = step(complete); % Calculate Steady-State error +sse = abs(1 - y(end)) + +xlim([0 3]) +ylim([0 3]) \ No newline at end of file