Fuzzy-rule emulated networks, based on reinforcement learning for nonlinear discrete-time controllers
This article introduces an adaptive controller for a class of nonlinear discrete-time systems, based on self adjustable networks called Multi-Input Fuzzy Rules Emulated Networks (MIFRENs), and its reinforcement learning algorithm. Because of the universal function approximation of MIFREN, the first...
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Format: | Journal |
Published: |
2018
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Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=50249134186&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/60297 |
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Institution: | Chiang Mai University |
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