Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/63438
Title: Adaptive single-neuron control system design based on fuzzy neural network model
Authors: Jia, L.
Tao, P.-Y.
Chiu, M.-S. 
Keywords: Adaptive control
Fuzzy neural network model
Nonlinear system
Single-neuron controller
Issue Date: Feb-2008
Source: Jia, L.,Tao, P.-Y.,Chiu, M.-S. (2008-02). Adaptive single-neuron control system design based on fuzzy neural network model. Huadong Ligong Daxue Xuebao /Journal of East China University of Science and Technology 34 (1) : 135-139+143. ScholarBank@NUS Repository.
Abstract: An adaptive single-neuron control system based on neuron-fuzzy model is proposed in this paper. Firstly, the nonlinear process model is identified by input-output points. Then the single-neuron controller, which is adjusted using the Lyapunov method, is considered so that the setpoint can be rapidly tracked by the output of the system. Theory analysis and simulation results show that the proposed single-neuron controller mimics the conventional PID controller. Consequently, it possesses simple structure and can be easily operated. Moreover, this adaptive single-neuron controller is better than conventional PID controller, and the parameters of the controller are on-line adjusted.
Source Title: Huadong Ligong Daxue Xuebao /Journal of East China University of Science and Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/63438
ISSN: 10063080
Appears in Collections:Staff Publications

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