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A neuro-mimetic dynamic scheduling algorithm for control: analysis and applications

H S Kwatra1, F J Doyle, I A Rybak

  • 1School of Chemical Engineering, Purdue University, West Lafayette, IN 47907-1283 USA.

Neural Computation
|April 1, 1997
PubMed
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This study analyzes a neuronal network model of the baroreceptor reflex, revealing a dynamic scheduled control mechanism for blood pressure regulation. This approach is validated for nonlinear process control applications.

Area of Science:

  • Neuroscience
  • Control Engineering
  • Biomedical Engineering

Background:

  • The baroreceptor reflex is crucial for blood pressure regulation.
  • Understanding its control mechanisms can inform advanced engineering applications.

Purpose of the Study:

  • To analyze a simple neuronal network model of the baroreceptor reflex.
  • To investigate its potential as a dynamic scheduled control mechanism.
  • To apply this model to nonlinear process control.

Main Methods:

  • Analysis of static and dynamic response characteristics of neurons and the network.
  • Investigation of the neuromimetic dynamic scheduled control function.
  • Application of control architectures derived from the model to process control case studies.

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Main Results:

  • The baroreceptor reflex model demonstrates a dynamic scheduled control mechanism.
  • Control Structure I, based on the baroreflex, was applied to conical tank level control.
  • Control Structure II, using set point error, was applied to a nonlinear continuous stirred tank reactor.

Conclusions:

  • The baroreceptor reflex model provides a validated dynamic scheduled control approach.
  • This approach is effective for nonlinear process control applications.
  • The study highlights the potential of neuromimetic control strategies.