DocumentCode
488514
Title
Neural Network Modeling and an Extended DMC Algorithm to Control Nonlinear Systems
Author
Hernandaz, Evelio ; Arkun, Yaman
Author_Institution
Department of Chemical Engineering, Georgia Institute of Technology, Atlanta, GA 30332-O100
fYear
1990
fDate
23-25 May 1990
Firstpage
2454
Lastpage
2459
Abstract
In this paper we propose a solution to the model predictive control problem for the case when the model is given by a nonlinear neural network. The solution follows the algorithm proposed by Peterson et al.[11] where the linear DMC is extended to handle nonlinear systems by updating the linear model with a `disturbance due to nonlinearities´ term. Simulation results of a reaction in a CSTR are included. Results show the improvement in control of the proposed algorithm over linear DMC.
Keywords
Active appearance model; Continuous-stirred tank reactor; Control system synthesis; Control systems; Neural networks; Nonlinear control systems; Nonlinear systems; Positron emission tomography; Predictive models; Tellurium;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 1990
Conference_Location
San Diego, CA, USA
Type
conf
Filename
4791169
Link To Document