Matlab Control System Toolbox Install
Miss Ruhnke
Control System Toolbox provides algorithms and apps for systematically analyzing, designing, and tuning linear control systems. You can specify your system as a transfer function, state-space, zero-pole-gain, or frequency-response model. Apps and functions, such as step response plot and Bode plot, let you analyze and visualize system behavior in the time and frequency domains.
You can tune compensator parameters using interactive techniques such as Bode loop shaping and the root locus method. The toolbox automatically tunes both SISO and MIMO compensators, including PID controllers. Compensators can include multiple tunable blocks spanning several feedback loops. You can tune gain-scheduled controllers and specify multiple tuning objectives, such as reference tracking, disturbance rejection, and stability margins. You can validate your design by verifying rise time, overshoot, settling time, gain and phase margins, and other requirements.
Create linear models of your control system as transfer functions, (sparse) state-space models, LPV and LTV models, and other representations. Discretize and resample models. Simplify analysis and control design by reducing model order.
Visualize system behavior in the time and frequency domain. Compute system characteristics such as rise time, overshoot, and settling time. Analyze system stability by computing gain and phase margins and crossover frequencies.
Interactively design and analyze single-input, single-output (SISO) controllers with the Control System Designer app, using automated tuning methods. Graphically tune common control components using root locus, Bode diagrams, and Nichols charts.
Design gain-scheduled controllers for nonlinear or time-varying plants. Specify requirements and automatically tune gain surface coefficients. Validate the tuning results across the entire operating range of your design.
Analyze and tune control systems modeled in Simulink and analyze its time and frequency domain characteristics using Simulink Control Design. Linearize Simulink models and compute time and frequency responses. Graphically or automatically tune feedback loops modeled in Simulink.
The python-control package is a set of python classes and functions thatimplement common operations for the analysis and design of feedback controlsystems. The initial goal is to implement all of the functionality requiredto work through the examples in the textbook Feedback Systems by Astrom and Murray. A MATLAB compatibility module isavailable that provides many of the common functions corresponding tocommands available in the MATLAB Control Systems Toolbox.
The python-control package can be installed using pip, conda or thestandard distutils/setuptools mechanisms. The package requires numpy andscipy, and the plotting routines require matplotlib. In addition, some routines require the slycot library in order to implementmore advanced features (including some MIMO functionality).
and verifying that no error message appears. It may be necessary to installslycot from source, which requires a working FORTRAN compiler and eitherthe lapack or openplas library. More information on the slycot packagecan be obtained from the slycot project page.
How would one check for installed MATLAB toolboxes in a script/function? (checking toolbox versions would also be good!) This could provide a quick and useful error message when someone attempts to run a script without a required toolbox.
Some quick searching revealed ver product or the license function with the 'test' argument may be useful, but I could not find a mapping of toolbox names (ie. 'Image Processing Toolbox') to product names (ie. 'control') or feature names (ie. image_toolbox).
This question was prompted by trying to test a co-workers script early. Unfortunately, it required the Image Processing Toolbox, which I currently lack. A useful error message would've saved time trying to diagnose the problem. Now I'll wait for a compiled version before testing it.
One drawback to the ver function is that it only tells you what's installed, not what has an available license. It's possible to have a toolbox installed and no license to use it (or all the available licenses could be checked out by other users). A better choice is the license function, which (as you pointed out) requires a unique "feature string" for each toolbox.
This covers many of the common ones, but isn't exhaustive and doesn't include feature strings for newer toolboxes. There doesn't appear to be any readily-available list of current feature strings for all MathWorks toolboxes. I believe you can find them on the "INCREMENT" lines in a license file, or (as vlee mentions in a comment) you can call a function from a given toolbox and then use license('inuse') to get the feature string from the displayed list of toolboxes currently being used. However, both of the above options require an available license already.
However, the above just confirms that the license exists, not that it can be checked out. The license could have expired or all the available licenses could be checked out by other users. To be absolutely certain that you will be able to use the available toolboxes, you can actually try to check out a license for the ones you need and test to see if you were successful. The following code attempts to check out a license for all the available toolboxes found above:
As Jason S mentions in a comment below, it's a bad idea to check out licenses willy-nilly, since they won't be released until you close MATLAB. You should only check out a license that you know you will need for a given application! Normally, licenses aren't checked out until you try to use a function from a given toolbox. For example:
The somefunction may fail for many reasons, for example that you lack available licenses or that the toolbox is not installed on your system. The try/catch allows you to abort gracefully and give the user a meaningful message as to exactly why it's not possible to perform the requested operation (right now).
The downside is that that is a less generic method. It lacks elegance and it is sensitive to namespace errors. The upside is that it tests if somefunction actually works. If it is used wisely it should grab hold of shared licenses only when you actually need them.
The python-control package is a set of python classes and functions thatimplement common operations for the analysis and design of feedback controlsystems. The initial goal is to implement all of the functionality requiredto work through the examples in the textbook Feedback Systems by Astrom and Murray. AMATLAB compatibility package (control.matlab) is available that providesmany of the common functions corresponding to commands available in theMATLAB Control Systems Toolbox.
The package requires numpy and scipy, and the plotting routines requirematplotlib. In addition, some routines use a module called slycot, which isa Python wrapper around some FORTRAN routines. Many parts of python-controlwill work without slycot, but some functionality is limited or absent, andinstallation of slycot is recommended. For more information, see the GitHubrepository for slycot.
A Toolbox is a library of MATLAB functions. Examples are theControl Systems Toolbox, the Signal Processing Toolbox. TheStudent Edition of MATLAB includes Signals and Systems Toolbox andthe Symbolic Toolbox. There are many user contributed matlab filesthat you can add to your MATLAB system to extend its capabilities (checkthe Mathworks Home Page)
Here I will assume that MATLAB has been already installed in the defaultdirectories in the Hard disk C: and we want to install a toolbox, calledMYTOOLS which consists of a set of M-files. First, we willcopy these files into a directory of the MATLAB system and then add itspath so that you can access these functions under MATLAB
This option will allow you to run MATLAB from personal systems in the same way as the PC section above, plus other University systems that are not located in the labs listed above. Note that our timeshare systems only allow connections from on campus; while it is possible to run this off-campus using UBVPN, but we don't recommend this because of slow performance when running graphical software over outside networks.
For graphical use from a Linux or Macintosh system, open a terminal window and log on to a "linux.eng.buffalo.edu" timeshare system using SSH with the "-X" option, eg. "ssh -X linux.eng.buffalo.edu". Enter your UBITname and password, then type "use matlab" at the prompt. Note that in some versions of Mac OS X the "X Window 11" software is not installed by default, and you might need to install it from your original OS CD or DVD.
In the lower-right corner of the task bar, known as the "notification area", you will see an X-Win32 2010 icon. Click on "Engineering Linux" to start a session on the SENS Linux timeshares. Note: If you get a windows that says "Do you want to accept this key?", click the "Accept" button.
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