Adaptive hierarchical fuzzy CMAC controller with stable learning algorithm for unknown nonlinear systems

Floriberto Ortiz, Wen Yu, Marco Moreno-Armendariz

Research output: Contribution to conferencePaperResearch

Abstract

In this paper, adaptive hierarchical fuzzy CMAC neural network controller (HFCMAC), for a certain class of nonlinear dynamical system is presented. The main advantages of adaptive HFCMAC control are: Better performance of the controller because adaptive HFCMAC can adjust itself to the changing enviroment and can be implemented in real time applications. The proposed method provides a simple control architecture that merges hierarchical structure, CMAC neural network and fuzzy logic. The input space dimension in CMAC is a time-consuming task especially when the number of inputs is huge this would be overload the memory and make the neuro-fuzzy system very hard to implement. This is can be simplified using a number of low-dimensional fuzzy CMAC in a hierarchical form. A new adaptation law is obtained for the method proposed, the overall adaptive scheme guarantees the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded. Simulation results for its applications to one example is presented to demonstrate the performance of the proposed methodology. © 2008 IEEE.
Original languageAmerican English
Pages294-304
Number of pages263
DOIs
StatePublished - 24 Dec 2008
EventProceedings - 2007 6th Mexican International Conference on Artificial Intelligence, Special Session, MICAI 2007 -
Duration: 24 Dec 2008 → …

Conference

ConferenceProceedings - 2007 6th Mexican International Conference on Artificial Intelligence, Special Session, MICAI 2007
Period24/12/08 → …

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nonlinear systems
Learning algorithms
learning
Nonlinear systems
Fuzzy neural networks
controllers
Controllers
fuzzy systems
Nonlinear dynamical systems
Fuzzy systems
feedback control
Closed loop systems
dynamical systems
Fuzzy logic
logic
methodology
Neural networks
Data storage equipment
simulation

Cite this

Ortiz, F., Yu, W., & Moreno-Armendariz, M. (2008). Adaptive hierarchical fuzzy CMAC controller with stable learning algorithm for unknown nonlinear systems. 294-304. Paper presented at Proceedings - 2007 6th Mexican International Conference on Artificial Intelligence, Special Session, MICAI 2007, . https://doi.org/10.1109/MICAI.2007.26
Ortiz, Floriberto ; Yu, Wen ; Moreno-Armendariz, Marco. / Adaptive hierarchical fuzzy CMAC controller with stable learning algorithm for unknown nonlinear systems. Paper presented at Proceedings - 2007 6th Mexican International Conference on Artificial Intelligence, Special Session, MICAI 2007, .263 p.
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Ortiz, F, Yu, W & Moreno-Armendariz, M 2008, 'Adaptive hierarchical fuzzy CMAC controller with stable learning algorithm for unknown nonlinear systems' Paper presented at Proceedings - 2007 6th Mexican International Conference on Artificial Intelligence, Special Session, MICAI 2007, 24/12/08, pp. 294-304. https://doi.org/10.1109/MICAI.2007.26

Adaptive hierarchical fuzzy CMAC controller with stable learning algorithm for unknown nonlinear systems. / Ortiz, Floriberto; Yu, Wen; Moreno-Armendariz, Marco.

2008. 294-304 Paper presented at Proceedings - 2007 6th Mexican International Conference on Artificial Intelligence, Special Session, MICAI 2007, .

Research output: Contribution to conferencePaperResearch

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Ortiz F, Yu W, Moreno-Armendariz M. Adaptive hierarchical fuzzy CMAC controller with stable learning algorithm for unknown nonlinear systems. 2008. Paper presented at Proceedings - 2007 6th Mexican International Conference on Artificial Intelligence, Special Session, MICAI 2007, . https://doi.org/10.1109/MICAI.2007.26