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Title: Adaptive neuro-fuzzy control of systems with unknown time delay
Authors: Ho, HF 
Rad, AB 
Wong, YK 
Lo, WL 
Issue Date: 2004
Publisher: Springer
Source: In TJ Tarn, SB Chen & C Zhou (Eds.), Robotic welding, intelligence and automation, p. 304-326. Berlin ; New York: Springer, 2004 How to cite?
Abstract: We present an adaptive fuzzy logic controller, which learns a lower-order model of the system via an on-line Neural Network (NN) identification algorithm. The identification is based on the estimation of parameters of a First-Order-Plus-Dead-Time (FOPDT) model. The outputs of the NN are three parameters: gain, apparent time delay and the dominant time constant. By combining this algorithm with a fuzzy logic controller with rotating rule-table, an adaptive controller is obtained which -with very little a priori knowledge- can compensate systems with unknown time delay. The simplicity and feasibility of the scheme for real-time control provides a new approach for a variety of real-time applications. Simulation and experimental results are included to demonstrate the adaptive property of the proposed scheme.
Description: International Conference on Robotic Welding, Intelligence and Automation (2002 : Shanghai, China)
ISBN: 3540208046
DOI: 10.1007/978-3-540-44415-2_19
Appears in Collections:Conference Paper

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