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A neuro-fuzzy approach to hybrid intelligent control
IEEE Transactions on Industry Applications, 1999This paper presents a neuro-fuzzy approach to the development of high-performance real-time intelligent and adaptive controllers for nonlinear plants. Several paradigms derived from cognitive sciences are considered and analyzed in this work, such as neural networks, fuzzy inference systems, genetic algorithms, etc. The different control strategies are
LAZZERINI B. +2 more
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Intelligent control using a neuro-fuzzy network
Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots, 2002Intelligent control techniques have emerged to overcome some deficiencies in conventional control methods in dealing with complex real-world systems. These problems include knowledge adaptation, learning, and expert knowledge incorporation. In this paper, a hybrid network that combines fuzzy inferencing and neural networks is used to model and to ...
Moenes Iskarous, Kazuhiko Kawamura
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Application of Neuro-Fuzzy Controller for Sumo Robot control
Expert Systems with Applications, 2011This paper proposes the application of Neuro-Fuzzy (NF) hybrid system for Sumo Robot (SR) control. This robot is frequently designed by engineering students for robotic competition. As the relation between sensors output signals and motors control pulses is highly nonlinear in SR, soft computing techniques can be used to define this nonlinear relation ...
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Adaptive Neuro-Fuzzy Sliding Mode Controller
International Journal of System Dynamics Applications, 2018A novel adaptive sliding mode controller using neuro-fuzzy network based on adaptive cooperative particle sub-swarm optimization (ACPSSO) is presented in this article for nonlinear systems control. The proposed scheme combines the advantages of adaptive control, neuro-fuzzy control, and sliding mode control (SMC) strategies without system model ...
Sana Bouzaida, Anis Sakly
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A reinforcement neuro-fuzzy combiner for multiobjective control
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 1999This paper proposes a neuro-fuzzy combiner (NFC) with reinforcement learning capability for solving multiobjective control problems. The proposed NFC can combine n existing low-level controllers in a hierarchical way to form a multiobjective fuzzy controller.
Chin-Teng Lin, I-Fang Chung
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Adaptive neuro-fuzzy control of dynamical systems
The 2011 International Joint Conference on Neural Networks, 2011In this paper, the an adaptive neuro-fuzzy control that combines the features of fuzzy sets and neural networks have been implemented and applied for the control of SISO and MIMO systems. Duffing forced oscillation system was considered as the SISO plant while the Twin Rotor laboratory set up that closely mimics helicopter dynamics was considered as ...
Alok Kanti Deb, Alok Juyal
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Adaptive Neuro-Fuzzy Controller for Synchronous Motor
2011 Developments in E-systems Engineering, 2011This paper presents an application of Adaptive Neuro-Fuzzy (ANF) control for synchronous motor (SM) speed. The ANF has the advantages of expert knowledge of the fuzzy inference system and the learning capabilities of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated.
Abdel Ghani Aissaoui +3 more
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Multirobot convoying using neuro-fuzzy control
Proceedings of 13th International Conference on Pattern Recognition, 1996In this paper real-time implementation of multirobot convoying behavior utilizing neuro-fuzzy control is presented. With only nine rules, the follower convoys the leader closely and smoothly by varying its speed and changing its direction. When the leader stops, the follower stops very close to the specified safe distance (within an inch). The follower
Kim C. Ng, Mohan M. Trivedi
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A neuro-fuzzy controller for underwater robot manipulators
2010 11th International Conference on Control Automation Robotics & Vision, 2010Autonomous underwater vehicles are increasingly replacing the prevalent remotely operated vehicle-manipulator systems. Most current generation AUVs are not fitted with manipulators and hence are mainly limited to underwater surveying and surveillance tasks because of the difficulty in the coordinated control of the resulting underwater vehicle ...
Shunmugham Raj Pandian +1 more
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Design method for neuro-fuzzy motion controllers
2002 IEEE International Conference on Industrial Technology, 2002. IEEE ICIT '02., 2003A four-step hybrid method for the design of neuro-fuzzy motion controllers is presented. The design method starts from a preliminary known good control strategy used as learning data. The aim of the method is to find a controller that reproduces as close as possible the good control strategy and ensures the accomplishment of the required motion for the
Ovidiu Popovici Vlad, Toshio Fukuda
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