Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/44109
標題: Evolutionary neural networks and DNA computing algorithms for dual-axis motion control
作者: Huang, C.H.
林俊良
Lin, C.L.
關鍵字: Evolutionary neural networks
DNA computing algorithm (DNACA)
Dual-axis
Cross-coupling
PID controllers
control design
groundwater remediation
optimization
system
platform
robots
期刊/報告no:: Engineering Applications of Artificial Intelligence, Volume 24, Issue 7, Page(s) 1263-1273.
摘要: A new method is proposed to deal with the dual-axis control of a multi-variables system with two induction motors. Investigation of resolving the cross-coupling problem of dual-axis platform is addressed by a neural net-based decoupling compensator and a sufficient condition ensuring closed-loop stability is derived. An evolutionary algorithm processing the universal seeking capability is proposed for finding the optimal connecting weights of the neural decoupling compensator and the gains of PID controllers. Extensive numerical studies verify the performance and applicability of the proposed design under a variety of operating conditions. (C) 2011 Elsevier Ltd. All rights reserved.
URI: http://hdl.handle.net/11455/44109
ISSN: 0952-1976
文章連結: http://dx.doi.org/10.1016/j.engappai.2011.06.013
Appears in Collections:電機工程學系所

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