DocumentCode :
2307677
Title :
Predictive multiple model switching control with the self-organizing map
Author :
Motter, Mark A.
Author_Institution :
NASA Langley Res. Center, Hampton, VA, USA
Volume :
4
fYear :
2000
fDate :
2000
Firstpage :
317
Abstract :
A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal
Keywords :
dynamics; minimisation; neurocontrollers; nonlinear control systems; predictive control; self-organising feature maps; codebook representation; dynamic regimes; global minimization; local dynamical regime; nonautonomous system; nonlinear autonomous systems; predictive multiple model switching control; self-organizing map local dynamic modeling; similarity metric; topological neighborhoods; Control system synthesis; Control systems; Lattices; NASA; Nonlinear control systems; Nonlinear dynamical systems; Postal services; Predictive models; Prototypes; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
ISSN :
1098-7576
Print_ISBN :
0-7695-0619-4
Type :
conf
DOI :
10.1109/IJCNN.2000.860791
Filename :
860791
Link To Document :
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