Virtual Control Lab
To support teaching, virtual experiments are made available here in order to make the content of the course "Automatic Control", in german "Regelungstechnik", understandable for students
General Information on Operation
The following applications are, amongst others, Matlab-Apps that were created with the Matlab-App-Designer. Version 2019b and newer is recommended.
The link leads you to detailed instructions on installing MATLAB.
If you click on the link of the respective app, you get a zip-folder in which all relevant files are located. These must be extracted.
Now open Matlab and select the desired extracted folder as "Current Folder". With a double-klick on the file “VCL_*.mlapp” the App-Designer opens.
Now you can start the application by a klick on the Run-Button.
You will also find the experiments as a Java-App in the folder. These can be run on any computer with installed Java runtime environment from version 6 update 32.
The Java-App can be opened directly in the folder.
A) Damped Single-Mass Oscillator
This application is intended to illustrate some important terms from automatic control engineering with the help of the simulation of a damped single-mass oscillator.
Amongst others, parameter changes have a direct effect on the system properties that can be observed. The goal is to make the relationships between the functional diagram, impulse and step response as well as the pole-/zero plot more tangible.
B) Frequency Response of the Damped Single-Mass Oscillator
This application is designed to demonstrate the meaning of the frequency response. For this, plots of the Bode diagram, the Nyquist plot, as well as the pole-/zero diagram of a damped single-mass oscillator are available.
When adjusting the parameters, amplitude and phase response change, as does the Nyquist plot. Thereby, the effects of the single parameters on the system become clear. In addition, the result of a harmonic input signal with the excitation frequency “omega” on the system output – the deflection of the mass – is shown in a time response plot.
C) Damped Single-Mass Oscillator with Linear Actuator for Position Control
A single-mass oscillator with a linear actuator for position control is shown. For control, P-, I-, and D- parameters can be enabled and adjusted.
Finally, the system behaviour can be examined in the presence of disturbances.
D) Controller Setting using the Bode Diagram
In this application, the stability criteria based on the simplified Nyquist criterion can be understood with the help of a Bode diagram. As plant model, a first-order lag element with delay, called PT1Tt , is used. The controller is of PI-type.
Both the plant and controller parameters can be varied within certain limits. The effects of the parameter changes on the amplitude and phase responses are immediately shown. For controller setting and stability test, the frequency ωπ will be determined automatically.
The main intention of this application is to help understanding the procedures performed when setting a controller based on the Bode diagram.
E) Inverse Pendulum
This applet visualizes an inverted pendulum.
The system consists of a DC servo motor that drives a linear guide on which the pendulum, mass m = 1.5 kg, length L = 1 m is mounted. The bearing used to mount the pendulum has a friction constant of B = 0.005 Nm*sec/rad. The full traveling distance is limited to 2.7 meters by means of two end switches. The goal of the control task is to keep the pendulum upright. This task can be mastered with a multiple control. For this purpose, a PD controller is used to control the position of the slide (x) and another PD controller is used to control the swivel angle of the pendulum (psi).
NOTE: This experiment is only available as a Java-App.
F) Bode Diagram versus Nyquist Plot
In this application, the Bode diagram and the Nyquist plot are compared face-to-face, in 2 different systems. This is demonstrated with the help of the frequency responses of a controller GR, a plant GS and their series connection GR* GS.
G) Convolution Integral
In this application, the solution of the convolution integral is shown for different combinations of the weight function g(t) and the input signal u(t).
If the parameters are changed, the solution of the convolution integral is calculated automatically. In addition, the application offers the opportunity to shift the folded input signal u(t-τ) as a function of time.