System Identification Toolbox - Continous or discrete model?
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Hello,
I want to identify a control process and have gathered samples of a thermocouple over time with a sample time of 1s.
My question is, which kind of model (continous or discrete) would I ideally use to estimate the process with the Identification Toolbox GUI?
From my understanding both could make sense. Discrete because my data is sampled and continous because the discrete data is derived from a
continous signal(falling and rising temperature).
Maybe you can help me to understand, what kind of model should be used in which situation?
Best regards
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Star Strider
2019-7-20
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It would seem to depend on your eventual application of the identified model. If you’re going to construct a completely analogue (continuous) system in hardware, identify it as such. If you are going to use sampled signals and implement a discrete controller, then identify it as a discrete system.
Also, I have nothing against the GUI, however it is likely easier to use the necessary functions themselves to generate the final identified model information. It depends on what you want to do with the results.
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Nils B
2019-7-20
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Star Strider
2019-7-20
As always, my pleasure.
I agree that identifying different models is preferable, and you will later have to determine if it is possible to combine them.
The GUI is convenient at the outset, as you describe, to explore the various options. However I have always used the functions to get the final results, since that is simply easier.
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