Avoiding Controller Singularities in Adaptive Recurrent Neural Control
| Authors: | Felix Ramon, FIME Universidad de Colima, Mexico
Sanchez Edgar N., CINVESTAV Guadalajara, Mexico
Loukianov Alexander G., CINVESTAV Guadalajara, Mexico |
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| Topic: | 3.2 Cognition and Control ( AI, Fuzzy, Neuro, Evolut.Comp.) |
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| Session: | Adaptive Neuro-fuzzy Control |
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| Keywords: | Induction Motors, Sliding Modes, Neural Control, Block Control |
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Abstract
In this paper, to overcome the controller singularity problems, a novel neural parameters adaptive law for on-line identification is proposed, such strategy avoid specific adaptive weights zero-crossing. Using a priori knowledge about the real plant, a recurrent neural network is proposed as identifier. Based on the neural identifier model, a discontinuous control law is derived, which combines Block Control and Sliding Modes. The proposed scheme is tested in a induction motor via simulations.
