Results 211 to 220 of about 17,567 (257)
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Neuro-fuzzy control of Quanser flexible link
2011 11th International Conference on Hybrid Intelligent Systems (HIS), 2011In this study, neuro-fuzzy control of Quanser flexible link system is presented. Since flexible link has an under actuated nature, the PD-like and importance-based neuro-fuzzy (NF) controllers have to control the hub position so that it can attenuate the tip deflections.
N. Nikpay +2 more
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Neuro-fuzzy tension controller for tandem rolling
Proceedings of the IEEE Internatinal Symposium on Intelligent Control, 2003A fuzzy logic controller (FLC) is designed to maintain constant tension for tandem rolling mills. By envisioning the fuzzy inference system as a neural network and introducing a tutor, a backward propagation algorithm is used as a self-organization technique for the FLC to approach the best parameters under supervision.
Farrokh Janabi-Sharifi, J. Liu
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Tuning of a neuro-fuzzy controller by genetic algorithm
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 1999Due to their powerful optimization property, genetic algorithms (GAs) are currently being investigated for the development of adaptive or self-tuning fuzzy logic control systems. This paper presents a neuro-fuzzy logic controller (NFLC) where all of its parameters can be tuned simultaneously by GA. The structure of the controller is based on the radial
Teo Lian Seng +2 more
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Neuro-fuzzy network control for a mobile robot
2009 American Control Conference, 2009A control structure that makes possible the integration of a kinematic controller and a neuro-fuzzy network (NFN) dynamic controller for mobile robots is presented. A combined kinematic/dynamic control law is developed using backstepping and stability is guaranteed by Lyapunov theory.
Jun Oh Jang, Hee-Tae Chung
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Application of on-line neuro-fuzzy controller to AUVs
Information Sciences, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tae Won Kim, Junku Yuh
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2013
Performance improvement of fuzzy logic controllers (FLC) can be achieved by adjusting the membership functions (MF). Neuro-fuzzy approaches are mostly used in such adjustment procedure, which involves several parameters of the MFs to be adjusted. In many cases, tuning the scaling factors gives the same performance as with MFs adjustment.
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Performance improvement of fuzzy logic controllers (FLC) can be achieved by adjusting the membership functions (MF). Neuro-fuzzy approaches are mostly used in such adjustment procedure, which involves several parameters of the MFs to be adjusted. In many cases, tuning the scaling factors gives the same performance as with MFs adjustment.
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Application of neuro-fuzzy control for satellite AOCS
7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002., 2004The attitude control of a future satellite is facing the challenge of its uncertain model because of flexural bodies coupling to the center body. This paper proposes a neuro-fuzzy approach to control the uncertain dynamics and disturbance. The flexible model of solar array is extended to the satellite attitude equation.
Jing Zhang +3 more
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1995
Neuronale Netze sind technische Abbilder von Nervensystemen, wie sie wesentlich fur die Gehirnfunktionen des Menschen (und naturlich auch anderer, hoher oder weniger hoch entwickelter Spezies) von Bedeutung sind. Ein Nervensystem besteht aus einer Vielzahl von miteinander “kommunizierenden” Nervenzellen, die als Neuronen bezeichnet werden.
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Neuronale Netze sind technische Abbilder von Nervensystemen, wie sie wesentlich fur die Gehirnfunktionen des Menschen (und naturlich auch anderer, hoher oder weniger hoch entwickelter Spezies) von Bedeutung sind. Ein Nervensystem besteht aus einer Vielzahl von miteinander “kommunizierenden” Nervenzellen, die als Neuronen bezeichnet werden.
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Adaptive neuro-fuzzy wheel slip control
Expert Systems with Applications, 2013Abstract Due to complex and nonlinear dynamics of a braking process and complexity in the tire–road interaction, the control of automotive braking systems performance simultaneously with the wheel slip represents a challenging problem. The non-optimal wheel slip level during braking, causing inability to achieve the desired tire–road friction force ...
Ćirović, Velimir, Aleksendrić, Dragan
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Plasma evolution control with neuro-fuzzy techniques
1999 European Control Conference (ECC), 1999In this paper one aspect of the plasma evolution control in tokamak (nuclear fusion) reactors is assessed, namely, the identification part of the controller. A fuzzy inference system (FIS) for plasma shape recognition applications is firstly presented. The model is directly extracted from a data set of examples of the problem in the absence of learning
Francesco Carlo Morabito, Mario Versaci
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