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Parameter Estimation for MIMO systems using Simulink Design Optimization

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I have created a first principles (mass and energy balance) model for a MIMO system of a reactive distillation column. It is an ODE (a set of first order differential equations) system which I solve using ode15s.
This system has multiple inputs which can be controlled by the plant operator (labelled in green) which are:
  • Heat Input to the reactor
  • Flow rate of raw materials feed into the reactor
  • Pressure at the top of the distillation column
  • Flow rate of the condensed product distillate from the column at the top
Similarly the entire system has multiple outputs as well (labelled in orange) which are:
  • The temperature of the reactor
  • The volume of the reactor
The first principles model is a non linear model and the parameters (which are constant i.e. not time varying) are not exactly known. I have lots of measurement data from the real plant and wish to estimate these parameters in order to fit the model simulation data to the real measured plant data. At present my simulation output follows the shape of the measured data roughly but is not exact which tells me that I can adjust the parameters to make it better.
However I saw in the tutorials for the simulink design optimization that it can be used for SISO systems. My question is, can it also be used to somehow estimate the params of MIMO systems using the Parameter Estimator App.

Answers (1)

Michael on 9 Sep 2022
Hello Kashan,
Yes, Parameter Estimator works with systems that have multiple inputs and outputs. When you define your experiment(s), you can specify which parts of your measured data are associated with which signals in the model.


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