Journal article
A Neuro-Mimetic Dynamic Scheduling Algorithm for Control: Analysis and Applications
Neural computation, v 9(3), pp 479-502
01 Mar 1997
PMID: 9097469
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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.
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Details
- Title
- A Neuro-Mimetic Dynamic Scheduling Algorithm for Control: Analysis and Applications
- Creators
- Harpreet S Kwatra - School of Chemical Engineering, Purdue University, West Lafayette, IN 47907-1283 USAFrancis J Doyle - School of Chemical Engineering, Purdue University, West Lafayette, IN 47907-1283 USAIlya A Rybak - Neural Computation Program, E.I. duPont de Nemours & Co., Wilmington, DE 19880-0328 USAJames S Schwaber - Neural Computation Program, E.I. duPont de Nemours & Co., Wilmington, DE 19880-0328 USA
- Publication Details
- Neural computation, v 9(3), pp 479-502
- Publisher
- MIT Press
- Number of pages
- 24
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Neurobiology and Anatomy
- Web of Science ID
- WOS:A1997WN04800001
- Scopus ID
- 2-s2.0-0031113207
- Other Identifier
- 991014877786904721
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- Collaboration types
- Industry collaboration
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Neurosciences