User`s guide

Modeling Multiple-Output Systems
Modeling Multiple-Output Systems
In this section...
“About Modeling Mu ltiple-Output Systems” on page 2-21
“Modeling Multiple O utputs Directly” on page 2-22
“Modeling Multiple Outputs as a Combination of Single-Output Models”
on page 2-22
“Improving Mu ltiple-Output Estimation Results by Weighing Outputs
During Estimation” on page 2-23
About Modeling Multiple-Output Systems
You can estimate mult iple-output model directly using all the inputs and
outputs, or you can try building models for subs ets of the most important
input and output channels. To learn more about each approach, see:
• “Modeling M ultiple Outputs Directly” on p age 2-22
• “Modeling Multiple Outputs as a Combination of Single-Output M odels”
on page 2-22
Modeling multiple-output systems is m ore challenging because input/output
couplings require additional parameters to obtain a good fitandinvolvemore
complex models. In general, a model is better when more data inputs are
included during modeling. Including more outputs typically leads to worse
simulation re su lts because it is harder to reproduce the behavior of several
outputs simultaneously.
If you know that some of the outputs have poor accuracy and should be
less important during estimation, you can control how much each output
is weighed in the estimation. For more information, see “Improving
Multiple-Output Estimat ion Results by Weighing Outp uts During
Estimation” on page 2-23.
2-21