Neural Computation, Vol 9, 479-502, Copyright © 1997 by The MIT Press
A Neuro-Mimetic Dynamic Scheduling Algorithm for Control: Analysis and Applications
Harpreet S. Kwatra, Francis J. Doyle III, Ilya A. Rybak and James S. Schwaber
A simple neuronal network model of the baroreceptor reflex is analyzed.
From a control perspective, the analysis suggests a dynamic scheduled
control mechanism by which the baroreflex may perform regulation of the
blood pressure. The main objectives of this work are to investigate the
static and dynamic response characteristics of the single neurons and the
network, to analyze the neuromimetic dynamic scheduled control function of
the model, and to apply the algorithm to nonlinear process control
problems. The dynamic scheduling activity of the network is exploited in
two control architectures. Control structure I is drawn directly from the
present model of the baroreceptor reflex. An application of this structure
for level control in a conical tank is described. Control structure II
employs an explicit set point to determine the feedback error. The
performance of this control structure is illustrated on a nonlinear
continuous stirred tank reactor with van de Vusse kinetics. The two case
studies validate the dynamic scheduled control approach for nonlinear
process control applications.
