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Dynamic neural networks based on-line identification and control of high performance motor drivesIn the automated and high-tech industries of the future, there wil be a need for high performance motor drives both in the low-power range and in the high-power range. To meet very straight demands of tracking and regulation in the two quadrants of operation, advanced control technologies are of a considerable interest and need to be developed. In response a dynamics learning control architecture is developed with simultaneous on-line identification and control. the feature of the proposed approach, to efficiently combine the dual task of system identification (learning) and adaptive control of nonlinear motor drives into a single operation is presented. This approach, therefore, not only adapts to uncertainties of the dynamic parameters of the motor drives but also learns about their inherent nonlinearities. In fact, most of the neural networks based adaptive control approaches in use have an identification phase entirely separate from the control phase. Because these approaches separate the identification and control modes, it is not possible to cope with dynamic changes in a controlled process. Extensive simulation studies have been conducted and good performance was observed. The robustness characteristics of neuro-controllers to perform efficiently in a noisy environment is also demonstrated. With this initial success, the principal investigator believes that the proposed approach with the suggested neural structure can be used successfully for the control of high performance motor drives. Two identification and control topologies based on the model reference adaptive control technique are used in this present analysis. No prior knowledge of load dynamics is assumed in either topology while the second topology also assumes no knowledge of the motor parameters.
Document ID
19960000403
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Rubaai, Ahmed
(Howard Univ. Washington, DC, United States)
Kotaru, Raj
(Howard Univ. Washington, DC, United States)
Date Acquired
September 6, 2013
Publication Date
August 1, 1995
Publication Information
Publication: NASA. Lewis Research Center, HBCUs Research Conference Agenda and Abstracts
Subject Category
Cybernetics
Accession Number
96N10403
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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