Control System I Lab Reports AUST, Lecture notes of Control Systems

Control System I Lab Reports AUST

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2017/2018

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Ahsanullah University of Science and Technology
Department of EEE
Course No: EEE-4106
Course Title: Control System-I Laboratory
Experiment No: 06
Experiment Name: Study of PID (Three-Term) Control System on a PC using
‘MATLAB’ Software.
Date of Performance: 15 July, 2018
Date of Submission: 22 July, 2018
ID:
15.01.05.130
15.01.05.131
15.01.05.132
15.01.05.133
15.01.05.134
Semester: 4.1
Section: C-1
Group: 05
pf3
pf4
pf5
pf8

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Ahsanullah University of Science and Technology

Department of EEE

Course No: EEE- 4106

Course Title: Control System-I Laboratory

Experiment No: 06

Experiment Name: Study of PID (Three-Term) Control System on a PC using

‘MATLAB’ Software.

Date of Performance: 15 July, 2018

Date of Submission: 22 July, 2018

ID:

Semester: 4.

Section: C- 1

Group: 05

Objectives:

 To meet the given specifications of Overshoot and Settling Time without

changing the pole of the system.

 To find the effect of Proportional Band, Integral Action and Derivative Action.

 To find the range of Kp for the system to be stable.

Theory:

A proportional–integral–derivative controller (PID controller) is a control loop feedback

mechanism. As the name suggests, PID algorithm consists of three basic coefficients:

proportional, integral and derivative which are varied to get optimal response.

Figure 1 : Block Diagram of a System with Three-Term Control

However in the sophisticated control system to improve the steady state and transient

performance respectively an integral and a derivative of the error (e) are added to the

proportional term to make a composite control or drive signal (u). Mathematically,

𝑐

𝑖

𝑑

Where, 𝑘

𝑐

, 𝑘

𝑖

𝑎𝑛𝑑 𝑘

𝑑

are gain of proportional, integral and derivative blocks respectively.

MATLAB Code

clc;

clear all;

close all;

k=0:0.001:10;

num=[0 1]; %taking kp=

den=conv([1 1],[1 2]);

rlocus(num,den,k);

G=0.707;

W=1.4142;

sgrid(G,W);

[kp,poles]=rlocfind(num,den);

[numc,denc]=cloop((kp)*num,den);

t=0:0.01:20;

step(numc,denc,t);

Note: System doesn’t meet the required specs.

For PI,

2

𝑝

𝑖

𝑝

MATLAB Code

clc;

clear all;

close all;

k=0:0.001:10;

num=[1 1]; %taking ki/kp=

den=conv(conv([1 1],[1 2]),[1 0]);

rlocus(num,den,k);

G=0.707;

W=1.4142;

sgrid(G,W);

[kp,poles]=rlocfind(num,den);

[numc,denc]=cloop((kp)*num,den);

t=0:0.01:20;

step(numc,denc,t);

Note: Tendency towards instability created.

Selected point = - 0.9914 + 1.0029i

Range of 𝒌 𝒑

: 0.0031 to ∞

Discussion:

In this experiment our goal was to fulfill the given specifications for the system without

changing the pole, which was successfully accomplished. We used integrator,

differentiator blocks which added extra pole to the system.

We obtained range of the Kp from the graph which is not exactly equal to the

theoretical value.

This difference between the theoretical and graphical value of Kp is because of our

selection point.

If we can select the point on graph more precisely we can get closer value of Kp to the

theoretical one.