Fig 1a: Here actuator along with Process model defines as plant
Figure 1: A typical control system ( Clarity of noise input just before the Plant model)
The first step is defining the plant in the form of a transfer function.
A typical plant is represented here in Laplace domain
Here the plant is second order system
Let us make the transfer function different for each student
K= day of birth = 23
T= month of birth= 10
For detail analysis the transfer function becomes
Now we model the plant using SIMULINK modeling
The value of K and T can be either defined in MATLAB command window
or we can explicitly define in the model as follows
Part 1 : Plant behavior without incorporating any control
The simulated plant with its output is shown below
For demand of 100 at time = 2 sec , we get a peak of 140 at around 9 sec , and the response settles down to 95 giving an steady state error of 5 %
Part 2: To improve the plant behavior Ist stem is to add an integral gain after error signal gets computed.
When we introduce proportional gain and set gain to 2
We find reduction in steady state error, from 5% to just 2%, but overshoot rises to 160
Part 3: Next improvement can be got if we introduce Integral gain along with proportional gain.
PI controller
Typically using PI controller steady state error can be further reduced but peak further rises to 170.
Part 4 and part 5: Finally we get more improvement if we implement PID controller and now we can also demonstrate the noise also gets fully taken care off.
To improve further we use a PID control
Here we have introduced derivative gain as 10, P=10 and integral gain as 0.2
We can see that there is no steady state error and overshoot is also reduced less than 20%
Let us now introduce a disturbance in the form of stem input, of 100 at time = 30 sec is introduced.
From the output we can see that plant has good disturbance removal property.
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