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Can I implement my own advanced control algorithm using Labview?

Hallo everybody??
 
Is it possible using Labview to implement my own advanced control algorithms instead of using the standard algorithms available in the tooboxes??
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Well, it depends on what you are going to do: which toolbox you need to adopt? Which toolbox functions you want to implement? Having more informations maybe I can help you more...

Best regards,

Fabio

Fabio M.
NI
Principal Engineer
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Hi again

 

I am working on an advanced model based control algorithm similar to the internal model control...I am in the process of developing this algorithm an I was wondering if there is a way that I can implement this algorithm to my benchmark process through labview instead for example through matlab that I am currently working on....

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A new feature in LabVIEW 8.20 is the Mathscript tool, which allows you work in an environment similar to Matlab and import your functions directly into LabVIEW.
 
I hope this will help you
 
Best regards,
 
Fabio
 
 
Fabio M.
NI
Principal Engineer
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Fabio mentioned the new MathScript feature of LabVIEW. MathScript offers general purpose text-based functions for signal processing and math functionality that you might find valuable.
For more specific functionality, you can extend LabVIEW with new functions for control design and analysis with the NI LabVIEW Control Design Toolkit. This Toolkit adds graphical and text-based (MathScript) functions to LabVIEW for jobs such as:
  • Calculate dynamic system characteristics such as DC gain, stability, norm, root locus, and pole-zero analysis
  • Analyze the frequency response of a a system model
  • Simulate the dynamic response of a discrete system model
  • Deploy a discrete model to a real-time target
  • Implement a discrete Kalman filter
  • Implement current and predictive observers
  • Create linear system models and modify the properties of a system model
  • Convert a system model:
    • From one representation to another
    • From a continuous-time to a discrete-time model
    • From a discrete-time to a continuous-time model
  • Obtain or set parameters, data, and names of a system model
  • Perform different types of linear system interconnections
  • Perform a zero-pole cancellation in transfer function and zero-pole-gain models or to reduce the number of states in state-space models
  • Calculate properties of a given state-space model, such as observability, detectability, controllability, stabilizability, similarity transformations, model balance, and system grammians
  • Calculate controller and observer gains for closed-loop state feedback control or to estimate a state-space model
  • Configure and test state-space controllers and state estimators in time domains
  • Construct, manipulate, and analyze stochastic state-space system models.
  • Create generic linear simulations and time domain plots for step inputs, impulse inputs, and initial condition response
 
For more general information about how you can apply LabVIEW to control design, please visit http://www.ni.com/labview/embeddedcontrol
 
--Sam
Sam Shearman
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