n4sid 'prediction' focus vs. n4sid 'simulation' focus
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Why are there 'prediction' or 'simulation' settings in n4sidOptions? I thought that subspace identification finds a state space realization directly from input/output data.
I tried toggling this option on the n4sid algorithm for my dataset and found that the state space matrices were identical between the 'prediction' focus and 'simulation' focus options.
Is there something that I am missing here?
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Chidvi Modala
2019-8-8
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As specified in the n4sid documentation, it estimates state space model using measured input-output data. The output represents the following system
xdot(t)=Ax(t)+Bu(t)+Ke(t)
y(t)=Cx(t)+Du(t)+e(t)
where e(t) is the disturbance
The model parameters are estimated by minimizing the error between the model output and measured response. The noise component is not trivial for n4sid. So ep(t) and es(t) are not equivalent. You can refer to https://www.mathworks.com/help/ident/ug/model-quality-metrics.html
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Chidvi Modala
2019-8-6
0 个投票
n4sid estimates state-space realization from input/output data. ‘prediction’ and ‘simulation’ settings in n4sidOptions determines the error to be minimized in the loss function during estimation.
‘prediction’ option focuses on minimizing error between measured and predicted outputs during estimation. ‘simulation’ option focuses on minimizing error between measured and simulation outputs during estimation.
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