Evolutionary Neural Networks and DNA Computing Algorithms for Decoupling Control Design of a Dual-Axes Motion Platform
碩士 === 國立中興大學 === 電機工程學系所 === 94 === This thesis presents a new approach to deal with the dual-axes control design problem of a two-input two-output multivariable system with induction motors. Investigation of resolving the cross-coupling problem of dual-axes platform is addressed by a neural net-ba...
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| Format: | Others |
| Language: | en_US |
| Published: |
2006
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| Online Access: | http://ndltd.ncl.edu.tw/handle/19264607616079455001 |
| Summary: | 碩士 === 國立中興大學 === 電機工程學系所 === 94 === This thesis presents a new approach to deal with the dual-axes control design problem of a two-input two-output multivariable system with induction motors. Investigation of resolving the cross-coupling problem of dual-axes 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 performance and applicability of our proposed design under a variety of operating conditions.
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