Neural Network Based Adaptive Output Feedback Control for Guided Munitions

This paper presents an approach to augmenting an existing controller with a neural network based adaptive element. The approach has advantage in the sense that augmentation of neural network does not require to design a new controller architecture like an inversion controller. The approach is illust...

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Bibliographische Detailangaben
1. Verfasser:	Nakwan Kim
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Adaptive control Adaptive systems Guided munitions Linear feedback control systems Neural network Neural networks Neurofeedback Nonlinear control systems Output feedback Programmable control Uncertainty Weapons
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Beschreibung
Zusammenfassung:	This paper presents an approach to augmenting an existing controller with a neural network based adaptive element. The approach has advantage in the sense that augmentation of neural network does not require to design a new controller architecture like an inversion controller. The approach is illustrated in an application of normal acceleration control for guided munitions
DOI:	10.1109/SICE.2006.315383