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This paper presents a novel adaptive tracking fuzzy control scheme for a class of nonlinear system. Takagi-Sugeno (T-S) fuzzy model is employed to approximate the unknown system function. Moreover, only one parameter is necessary to be tuned online such that the complexity of the controller is reduced dramatically. All the signals in the closed-loop system is shown to be ultimately uniformly bounded,...
This paper proposes an adaptive proportional-integral-derivative (PID) controller which integrates the fuzzy sets with the Cerebella Model Articulation Controller (CMAC). Three gain parameters of PID controller, constructed by three fuzzy CMAC (FCMAC) models, are real-time modified in the sense of adaptation to solve the tracking control problem of a class of nonlinear systems. The proposed PID controller...
An Adaptive Fuzzy PID Controller with Genetic Algorithm (GA) to tune its parameters is proposed by this paper. The task of the controller is to track the trajectory of a nonlinear system as best as it could. The Lyapunov's direct method is used as a tool for nonlinear system analysis and design. In which, the Lyapunov's linearization method is proven here to be useful for linear control. The paper...
In this paper, a wavelet-neural-based adaptive control (WNBAC) with a PI type learning algorithm is proposed. The proposed WNBAC system is composed of a wavelet neural controller and a fuzzy compensation controller. The wavelet neural control is utilized to approximate an ideal controller and the fuzzy compensation controller with a fuzzy logic system in it is used to remove the chattering phenomena...
This paper presents the design of an indirect adaptive fuzzy sliding mode controller for a vector controlled induction motor position servo drive. The proposed adaptive controller takes advantage of sliding mode control (SMC) and proportional integral (PI) control. The chattering effect is attenuated and robust performance can be ensured. Moreover, the upper bound of the discontinuous control term...
The adaptive controller for a class of nonlinear discrete-time systems based on multi-input fuzzy rules emulated network (MIFREN) is introduced in this article. MIFREN is assigned to identify the unknown plant under control, then a novel control law is introduced based the previously identified plant with another MIFREN. All control parameters, including the learning rates are selected to guarantee...
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