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This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions...
The DC-DC converters are used extensively in personal computers, computer peripherals, and adapters of consumer electronic devices to provide a fixed DC voltage. From the control viewpoint, the controller design must cope with their wide input voltage and load resistance variations to ensure the stability in any operating condition while providing fast transient response. For many years, the control...
This paper proposes a novel method of on-line modeling and control through the Takagi-Sugeno (T-S) fuzzy-neural model for a class of general n-link robot manipulators. Compared with the previous method, the main contribution of this paper is an investigation of the more general robot systems using on-line adaptive T-S fuzzy-neural controller. Specifically, the general robot systems are exactly formed...
An intelligent tracking control using a dynamic fuzzy neural network (DFNN) is proposed in this paper. The intelligent tracking control system is comprised of a computation controller and a robust controller. The computation controller containing a DFNN identifier is the principal controller, and the robust controller is designed to achieve L2 tracking performance. The DFNN identifier uses the structure...
This paper proposes an intelligent tracking control for the chaotic systems via backstepping approach. The intelligent tracking control system is comprised of a neural controller and a robust controller. The neural controller containing a self-organizing fuzzy neural network (SOFNN) identifier is the principal controller, and the robust controller is designed to dispel the effect of minimum approximation...
For many years, the control approaches for the dc-dc power converters are limited to PI controller structures. However, it gives the overshoot in output voltage as the rise time of response is reduced. To tackle this problem, an adaptive recurrent fuzzy neural network (ARENN) control system is developed in this paper. The on-line adaptive laws of the ARENN control scheme are derived based on the Lyapunov...
This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In proposed approach, the receiver states can be reconstructed...
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