Search Results - fuzzy/neural approximators

Petri type 2 fuzzy neural networks approximator for adaptive control of uncertain non-linear systems by Bibi, Youssouf, Bouhali, Omar, Bouktir, Tarek

“…In this study, the authors developed a novel universal approximator by the integration of Petri networks into type 2 fuzzy neural networks (T2FNN…”
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Adaptive backstepping control for flexible-joint manipulator using interval type-2 fuzzy neural network approximator by Dian, Songyi, Hu, Yi, Zhao, Tao, Han, Jixia

“… controllers based on type-1 fuzzy neural network approximator and neural network approximator…”
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A Simplified Fuzzy Wavelet Neural Control for Nonlinear Systems With Quantized Inputs and Deferred Constraints by Yue, Xiaohui, Zhang, Huaguang, Sun, Jiayue, Liu, Xin

“… Then, to allow for a reduced computational cost concerning fuzzy/neural approximators, a single parameter updating based fuzzy wavelet neural network is devised to approximate the unknown…”
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Adaptive Fuzzy Wavelet Neural Network Event-Triggered Consensus Tracking Control for Networked Hyperbolic PDE-ODE Systems by Zheng, Yukan, Yao, Xiangqian, Liu, Yu

“…In this article, the event-triggered consensus tracking control problem is explored for a network of hyperbolic partial differential equations (PDEs) with…”
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A fuzzy neural network approximator with fast terminal sliding mode and its applications by Yu, Shuanghe, Yu, Xinghuo, Man, Zhihong

“…This paper presents a new training method for fuzzy neural network (FNN) systems to approximate unknown nonlinear continuous functions…”
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H(infinity) tracking-based sliding mode control for uncertain nonlinear systems via an adaptive fuzzy-neural approach by Wang, Wei-Yen, Chan, Mei-Lang, Hsu, C J, Lee, Tsu-Tian

“…A novel adaptive fuzzy-neural sliding-mode controller with H(infinity) tracking performance for uncertain nonlinear systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors…”
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Experimental Investigation of an Adaptive Fuzzy-Neural Fast Terminal Synergetic Controller for Buck DC/DC Converters by Babes, Badreddine, Hamouda, Noureddine, Albalawi, Fahad, Aissa, Oualid, Ghoneim, Sherif S. M., Abdelwahab, Saad A. Mohamed

“… A Fuzzy Neural Network (FNN) structure is exploited here to approximate the unknown converter nonlinear dynamics due to changes in the input voltage and loads…”
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Robust Direct Adaptive Controller for a Class of Uncertain Nonlinear Systems Using Petri Type 2 Fuzzy Neural Networks (PT2FNN) as a New Approximator by Bibi, Youssouf, Bouhali, Omar, Bouktir, Tarek

“… Within this scheme, the Petri Type 2 Fuzzy Neural Networks (PT2FNN) are employed to approximate an unknown ideal controller, that can achieve control objectives…”
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Fuzzy Neural Pseudo Control With Prescribed Performance for Waverider Vehicles: A Fragility-Avoidance Approach by Bu, Xiangwei, Lv, Maolong, Lei, Humin, Cao, Jinde

“… Furthermore, fuzzy neural approximators are combined with the adaptive compensation strategy to resist both system uncertainties and external disturbances…”
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Emerging Technologies towards Energy Cooperation between Smart Grid and Microgrids

“…The growing propagation of microgrids and their remarkable effects on the operation of the smart grid is leading to the development of a sustained environment…”
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Robust adaptive fuzzy-neural control of nonlinear dynamical systems using generalized projection update law and variable structure controller by Wang, W Y, Leu, T G, Hsu, C C

“…In this paper, a robust adaptive fuzzy-neural control scheme for nonlinear dynamical systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbance, and modeling errors…”
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Observer-based dynamic surface control for flexible-joint manipulator system with input saturation and unknown disturbance using type-2 fuzzy neural network by Hu, Yi, Dian, Songyi, Guo, Rui, Li, Shengchuan, Zhao, Tao

“…) with interval type-2 fuzzy neural network (IT2FNN) approximator is proposed for flexible-joint manipulator with the input saturation and unknown nonlinear disturbance…”
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Are regular fuzzy neural nets universal approximators? by Buckley, J.J., Hayashi, Y.

“…We argue that if fuzzy neural nets use fuzzy arithmetic based on the extension principle they cannot be universal approximators…”
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Trajectory Tracking Control Method for Omnidirectional Mobile Robot Based on Self-Organizing Fuzzy Neural Network and Preview Strategy by Zhao, Tao, Qin, Peng, Zhong, Yuzhong

“…). Considering the influence of uncertainty on tracking accuracy, a self-organizing fuzzy neural network approximator (SOT1FNNA…”
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Self-Constructing Adaptive Robust Fuzzy Neural Tracking Control of Surface Vehicles With Uncertainties and Unknown Disturbances by Wang, Ning, Joo Er, Meng

“… neural approximator by generating and pruning fuzzy rules, and achieve accurate approximation; 2) an adaptive approximation-based controller…”
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A Novel Fuzzy Neural Network Approximator with Exponential Fast Terminal Sliding Mode by Ming He, Yunfeng Liu, GuangBin Liu, Huafeng Liu

“…A new learning algorithm for fuzzy neural network (FNN) systems to approximate unknown nonlinear continuous functions is proposed…”
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Interval type-2 fuzzy neural network-based adaptive compensation control for omni-directional mobile robot by Qin, Peng, Zhao, Tao, Dian, Songyi

“…), a new adaptive trajectory tracking control scheme based on interval type 2 fuzzy neural network approximator (IT2FNNA…”
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A Beta basis function Interval Type-2 Fuzzy Neural Network for time series applications by Baklouti, N., Abraham, A., Alimi, A.M.

“… Neuro fuzzy systems have been proved to be excellent universal approximators. In this paper we propose a new based function Interval Type-2 Fuzzy Neural Network denoted…”
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Speed tracking control for hydraulic transformer system based on active regulating common pressure rail by Shen, Wei, Shen, Chao, Su, Xiaoyu

“… Besides, due to the strong non-linear characteristics of the proposed system, the pi-sigma fuzzy neural network is employed as the function…”
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A fuzzy neural network approximator with fast terminal sliding mode and its applications by Shuanghe Yu, Xinghuo Yu, Zhihong Man

“…This paper presents a novel training method for fuzzy neural network (FNN) systems to approximate unknown nonlinear continuous functions…”
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