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PIDDESIGN
R20150513
Software description
PIDDESIGN is a software for simple stepresponsebasedidentification, fast PID controller tuning and effective quality test using simulation of control.
If you use the software PIDDESIGN for research purposes, we would be happy to hear about it. Please let us know at juraj.oravec@stuba.sk.
BibTeX entry for citation:
@inproceedings{piddesign,
author = {Oravec, J. and Bako\v{s}ov\'a, M.},
title = {{PIDDESIGN}  Software for PID Control Education},
booktitle = {IFAC Conference on Advances in PID Control},
url = {https://bitbucket.org/oravec/piddesign/wiki/},
year = {2012},
}
Software localization
The software is recently localized into following languages:

English

Slovak
Software compatibility
The software has been created in MATLABSimulink programming environment and uses its graphical user interface to make software more interactive. Therefore it can be run in MATLAB v7  Simulink v6.5 and newer.
Software installation
To install the software in a successful way, go through the following seven steps:
Step 1: Download the software package from the link: https://bitbucket.org/oravec/piddesign/downloads
Step 2: Unzip the package into the required homefolder (e.g.: MATLAB/toolbox/piddesign)
Step 3: Run MATLAB
Step 4: In the MATLAB menu use File/Set Path...
Step 5: Use button [Add with Subfolders...]
Step 6: Find out the chosen homefolder
Step 7: Use button [Save] to save the changes.
Alternatively, you can use tbxmanager to install PIDDESIGN by typing:
tbxmanager install piddesign
tbxmanager update piddesign
Software initialization
The software can be run in MATLAB command window by typing: "piddesign" Then the main window of software is opened.
Software termination
It is recommended to shut down the software using the possibility "Shut Down" in the "Setup" menu.
Identification
Using the button [Identification] of the main window, the new window is open. The next window offers three identification possibilities:

Step Response Data – enables to identify the controlled process directly from the data file. Data are obtained from the measured and recorded step response.

Load the Data File – enables to run identification from the data stored in an external data file.

Process Model Data – enables to identify process model with required properties of the transfer function.
Step Response Data
Two windows are opened. First one contains figure with step response of output variable y(t) and control input u(t). The second one contains a table where the user must enter parameters of the identified process.
You can choose between two types of step responses:

Aperiodic

Damped Periodic

Nonminimal phase

1st Order System

1st or 2nd Order System
Aperiodic
You must enter input parameters:

u_0 – initial value of the input variable u(t)

u_Inf – final value of input variable u(t) * y_0 – initial value of output variable y(t)

y_Inf – final value of output variable y(t)

t_0 – the time of the step response

t_D – the time of the change of the output variable i.e. time delay

t_1 – the time corresponding to the tangent step response inflex point in the parameter y_0

t_2 –the time corresponding to the tangent step response inflex point in the parameter y_Inf

Sim_Time – simulation time
When all parameters are specified, use button [Identification]. The new window with 2 options of step response types is opened:

1st Order System

n – th Order System
Using the button [1st Order System], the software makes the identification by the Strejc method to obtain aperiodic model by approximation by 1st order system.
Using the button [nth Order System], the software makes the identification by the Strejc method to obtain the aperiodic model, but this model cannot be described by 1st order transfer function.
Then 3 windows are opened:
First one contains figure with step response of output variable y(t) and the tangent line.
The second one contains parameters of identified process and button [Controller Tuning]. Using this button process of controller tuning will start (see the section "Controller Tuning")
Third one contains 3 other options:

Identification Tuning – you can receive the transfer function, which generates the step response that covers the original one more precisely. The difference between the original step response and the step response obtained by the identification using the modified position of the tangent is directly displayed as a red area in the new window.

Comparison – software compares the original and identified step response graphically and analytically.

Get lower order model – you can receive the transfer function of the system by approximation of identified model by lower order model.
Damped periodic
You must enter input parameters:

u_0 – initial value of the input variable u(t)

u_Inf – final value of input variable u(t)

y_0 – initial value of output variable y(t)

y_Max – maximum value of the output variable y(t)

y_Min  minimum value of the output variable y(t), which follows y_Max * y_Inf – final value of output variable y(t)

t_0 – the time of step response

t_D – the time of the change of the output variable i.e. time delay

t_Max –time which corresponds to y_Max

t_Min  time which corresponds to y_Min

Sim_Time – simulation time
When all parameters are specified, use button [Identification]. Then 3 windows are opened:
First one contains figure with step response of output variable y(t).
The second one contains parameters of identified process and button [Controller Tuning]. By using this button process of controller tuning will start (see the section "Controller Tuning").
Third one contains 2 other options:

Identification Tuning – you can receive the transfer function, which generates the step response that covers the original one more precisely. The difference between the original step response and the step response obtained by the identification using the modified position of the tangent is directly displayed as a red area in the new window.

Comparison – software compares the original and identified step response graphically and analytically.
Nonminimal phase
You must enter input parameters:

u_0 – initial value of the input variable u(t)

u_Inf – final value of input variable u(t)

t_0 – the time of step response

t_D – the time of the change of the output variable i.e. time delay

y_0 – initial value of output variable y(t)

t_Min – time which corresponds to y_Min

y_Min  minimum value of the output when the gain is greater than 0 (or the maximum, if gain is less than 0)

t_47 – time which corresponds to y_47

y_47 – output value of 47% gain

t_90 – time which corresponds y_90

y_90 – output value of 90% gain

y_Inf  final value of output variable y(t) * Sim_Time – simulation time
When all parameters are specified, use button [Identification]. Then 2 windows are opened:
First one contains figure with step response of output variable y(t).
The second one contains parameters of the identified process. 1st Order System You must enter input parameters:

u_0 – initial value of the input variable u(t)

u_Inf – final value of input variable u(t)

t_0 – the time of step response

t_D – the time of the change of the output variable i.e. time delay

y_0 – initial value of output variable y(t)

t_30 – time which corresponds to y_30

y_30  output value of 30% gain

t_70  time which corresponds to y_70

y_70  output value of 70% gain * y_Inf – final value of output variable y(t)

Sim_Time – simulation time
When all parameters are specified, use button [Identification]. Then 3 windows are opened:
First one contains figure with step response of output variable y(t).
The second one contains parameters of identified process and button [Controller Tuning]. Using this button process of controller tuning will start (see the section "Controller Tuning") Third one contains 3 other options:

Identification Tuning – you can receive the transfer function, which generates the step response that covers the original one more precisely. The difference between the original step response and the step response obtained by the identification using the modified position of the tangent is directly displayed as a red area in the new window.

Comparison – software compares the original and identified step response graphically and analytically.

Get lower order model – you can receive the transfer function of the system by approximation of identified model by lower order model (lower than 1 does not exist)
1st or 2nd Order System
You must enter input parameters:

n – system order (possibility to choose the 1st or the 2nd order system)

u_0 – initial value of the input variable u(t)

u_Inf – final value of input variable u(t)

t_0 – the time of step response

t_D – the time of the change of the output variable i.e. time delay

y_0 – initial steadystate value of the output variable

t_33 – time which corresponds to the value of output of 33% gain

t_70  time which corresponds to the value of output of 70% gain

y_Inf – final value of output variable y(t)

Sim_Time – simulation time
When all parameters are specified, use button [Identification]. Then 3 windows are opened:
First one contains figure with step response of output variable y(t).
The second one contains parameters of identified process and button [Controller Tuning]. Using this button process of controller tuning will start (see the section "Controller Tuning").
Third one contains 3 other options:

Identification Tuning – you can receive the transfer function, which generates the step response that covers the original one more precisely. The difference between the original step response and the step response obtained by the identification using the modified position of the tangent is directly displayed as a red area in the new window.

Comparison – software compares the original and identified step response graphically and analytically.

Get lower order model – you can receive the transfer function of the system by approximation of identified model by lower order model (lower than 1 does not exist).
Load the Data File
The program opens the new window, where the user can comfortably find out a required data file containing recorded stepresponse data. The considered structure of the data file is as follows, the first column vector represents a time and the second column vector represents associated measured values of the output variable.
Next window shows a figure of the step response. Another window requires entering the parameter for normalization:

t_0 – the time of the step change

delta_u – size of the step change
Use the button [Normalization]. Next window shows a figure of normalized step response.
In the next window, there is a choice of data processing:

Filtration

Identification
To obtain the aperiodic model of the controlled process, the user can directly use the button [Identification]. When the damped periodic model is required, the user can simply activate the checkbox [Periodic process] and then use the button [Identification]. If the controlled process has been identified using the Strejc method, the tangent to the step response is also depicted and its equation is given.
Filtration
If the loaded step–response data are noisy, the user can use the filtration before identification, simply using the button [Filtration]. Then the new window for filtration is opened. You must enter input parameters:

order – order of the filter n

omega – filter frequency (values from [0;1])
User gets:
 Filtration error – difference between filtered signal and origin
All entered parameters are needed to count parameters of the filter a, b. These coefficients can be counted by using different methods. It is possible to design nonrecursive filter parameters (FIR). Types of the recursive filter (IIR):

Butterworth

Chebyshev

Chebyshev inv.

elliptical
With regard to the frequency of affecting the measured signal can be selected from various types of the proposed filter:

lowpass

highpass

bandstop
There is a choice of the method of filtration:

simple

improved
After filtration software automatically displays a graph of filtered and unfiltered signal for easier visual evaluation of filtration.
By using the button [Save], the user can simply store reached filtered data into the new data file for later usage. After filtration, identification can be started.
Process Model Data
The program opens a new window for the transfer function of the known parameters of the model. User can choose type of the transfer function

General transfer function

Aperiodic

Damped Periodic
General transfer function
You must enter input parameters:

NUM  numerator of the model system transfer function

DEN  denominator of the model system transfer function

D – time delay

Sim_Time – simulation time
To obtain the aperiodic model of the controlled process, the user can directly use the button Identification. When the damped periodic model is required, the user can simply activate the checkbox [Periodic process] and then use the button [Identification].
Results of the identification will be displayed in new windows.
Aperiodic
You must enter input parameters:

n  order

K  gain

T  time constant

Sim_Time – simulation time
Software makes the identification by the Strejc method to obtain aperiodic model by approximation using the lower order system if required. Results of the identification will be displayed in new windows
Damped Periodic
You must enter input parameters:

K  gain

T_pe  time constant

ksi_pe  damping coefficient  values from an interval [0;1]

D_pe  time delay

Sim_Time  simulation time
Results of the identification will be displayed in new windows.
Controller Tuning
Using the button [Controller Tuning] of the main window, the new window for controlled system parameters design will be opened.
Choose a type of the system on the upper side of the window. There are two options:
 Transfer function by Strejc The aperiodic process can be described using transfer function by Strejc in (1)
G = K/(Ts + 1)^nexp(  D*s) (1)
Inputs of the transfer function by Strejc:

n  order

K  gain

T  time constant

D  time delay
Damped periodic transfer function
The damped periodic process can be described using the associated parameters of the transfer function in (2).
G_pe = K/(T_pe^2s + 2ksi_peT_pes + 1)exp(  D_pes) (2)
Inputs of the damped periodic transfer function:

K  gain

T_pe  time constant

ksi_pe  damping coefficient  values are an open interval (0;1)

D_pe  time delay
Using the button [Controller Tuning] opens the new window for PID controller tuning. The required type of the PID controller can be chosen using the associated radiobutton:

P

PI

PID

PD
and choosing the radiobutton of the required class of controller tuning methods:

Experimental methods

Analytical methods
Using the popup menu enables to choose from the list of the available methods.
Using the button [Controller tuning] the controller with the set properties will be designed. A new window for control performance check using the simulation of control will be opened.
PID Controller Parameters
In the upper left part of the window are shown the calculated parameters of the designed controller in (3)
Gr = (Z_Rs + Z_R/T_I + Z_RT_D*s^2)/s (3)
Input & Output parameters:

Z_R  proportional gain

T_I  integral time constant

T_D  derivative time constant

T_R – antiwindup gain parameter of an integral part

T_D  filter of the derivative part
Process Model
In the upper right part are shown the parameters of the controlled system in (4)
G = NUM/DENexp(  Ds) (4)
Input & Output parameters:

NUM  numerator of the controlled system transfer function

DEN  denominator of the controlled system transfer function

D  time delay of the controlled system
Setpoint w(t)
In the middle left part of are shown the parameters for the setpoint tracking. Input parameters:

W_Initial  initial value of set point

W_Final  final value of set point

W_Step_Change  time of the step change
Disturbance r(t)
In the middle right part of are shown the parameters for the disturbance rejection.
Input parameters:

R_Initial  initial value of disturbance

R_Final  final value of disturbance

R_Step_Change  time of the step change
Simulation parameters
In the upper right part are shown simulation parameters Input parameters:

Control_Precision  tolerance of the setpoint neighborhood

Sim_Time  simulation time

U_Min_Boundary  lower constraint on the control input

U_Max_Boundary  upper constraint on the control input
Using the button [Step response] the simulation of control will be started.
Then the various figures are opened:

poles and zeros of the closed loop transfer function

control performance of the controlled output

associated control input with and without saturation generated by the tuned controller
Also the new window with various calculated quality criteria. The background color indicates the relative property of the value. The green background color indicates suitable value, the yellow color medium, and the red color is used for relatively high value. These colorbased decisions have just informative significance.
Quality Criteria
Output parameters:

Settling_Time  settling time

Max_Overshoot  maximal overshoot [%]

IAE

ISE

ITAE

ITSE

ISTAE

ISTSE

ISE_u

ISE_du

ISE_de
Using the button [Back] the previous window will be returned.
Software Settings
In the main window of the software, you can press the [Setup] button, which opens a new window. It contains 4 options:
[Shut Down] – properly shut down the program and saved some settings, such as the language preferences or color effects.
[Reset]  restart the program PIDDESIGN.
[Close Graphs]  close all windows with depicted graphs, which can be used when longer work with the program is necessary.
[Help] – runs file „help.html“.
Illustrative Examples
Example 1.1
PID controller tuning for controlled system described by the known transfer function
Using the button [Controller Tuning] of the main window, the new window for controlled system parameters design will be opened. The aperiodic process can be described using transfer function by Strejc (1). The damped periodic process can be described using the associated parameters of the transfer function (2).
G = K/(Ts + 1)^nexp(  D*s) (1)
G_pe = K/(T_pe^2s + 2ksi_peT_pes + 1)exp(  D_pes) (2)
Inputs of the transfer function by Strejc:

n  order

K  gain

T  time constant

D  time delay
Inputs of the damped periodic transfer function:

K  gain

T_pe  time constant

ksi_pe  damping coefficient  values from [0;1]

D_pe  time delay
Using the button [Controller Tuning] opens the new window for PID controller tuning. The required type of the PID controller can be chosen using the associated radiobutton:

P

PI

PID

PD
and choosing the radiobutton of the required class of controller tuning methods:

Experimental methods

Analytical methods
Using the popup menu enables to choose from the list of the available methods.
Using the button [Controller tuning] the controller with the set properties will be designed. A new window for control performance check using the simulation of control will be opened. In the upper left part of the window, the calculated parameters of the designed controller (3) are shown.
Gr = (Z_Rs + Z_R/T_I + Z_RT_D*s^2)/s (3)
PID Controller Parameters
Input & Output parameters:

Z_R  proportional gain

T_I  integral time constant

T_D  derivative time constant

T_R  antiwindup parameter of an integral part

T_D  filter of the derivative part
In the upper right part are shown the parameters of the controlled system (4).
G = NUM/DENexp(  Ds) (4)
Process Model
Input & Output parameters:

NUM  numerator of the controlled system transfer function

DEN  denominator of the controlled system transfer function

D  time delay of the controlled system
In the middle left part of are shown the parameters for the setpoint tracking.
Setpoint w(t)
Input parameters:

W_Initial  initial value of set point

W_Final  final value of set point

W_Step_Change  time of the step change
In the middle right part of are shown the parameters for the disturbance rejection.
Disturbance r(t)
Input parameters:
 R_Initial  initial value of disturbance
 R_Final  final value of disturbance
 R_Step_Change  time of the step change
In the upper right part are shown
Simulation parameters
Input parameters:

Control_Precision  tolerance of the set point

Sim_Time  simulation time

U_Min_Boundary  lower constraint of the control input

U_Max_Boundary  upper constraint of the control input
Using the button [Step response] the simulation of control will be started.
Then the various figures are opened:

poles and zeros of the closed loop transfer function

control performance of the controlled output

associated control input generated by the tuned controller
And the new window with various calculated quality criteria. The background color indicates the relative property of the value. The green background color indicates suitable value, the yellow color medium, and the red color is used for relatively high value. These colorbased decisions have just informative significance.
Quality Criteria
Output parameters:

Settling_Time  settling time

Max_Overshoot  maximal overshoot [%]

IAE

ISE

ITAE

ITSE

ISTAE

ISTSE

ISE_u

ISE_du

ISE_de
Using the button [Back] the previous window will be returned.
Updated