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|Title:||Adaptive neural network control of helicopters||Authors:||Ge, S.S.
|Issue Date:||2006||Citation:||Ge, S.S.,Tee, K.-P. (2006). Adaptive neural network control of helicopters. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3973 LNCS : 82-87. ScholarBank@NUS Repository.||Abstract:||In this paper, we propose robust adaptive neural network (NN) control for helicopter systems by using the Implicit Function Theorem and the Mean Value Theorem, which are useful tools for handling non-linear nonaffine systems. We focus on single-input single-output (SISO) helicopter systems, which are exemplified by certain single-channel modes of operation, such as vertical flight and pitch regulation, and also by special conditions under which the multiple channels become decoupled. It is shown that under the proposed NN control, the output tracking error converges to a small neighbourhood of the origin, while all closed loop signals are Semi-Globally Uniformly Ultimately Bounded (SGUUB). © Springer-Verlag Berlin Heidelberg 2006.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/69199||ISBN:||3540344829||ISSN:||03029743|
|Appears in Collections:||Staff Publications|
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