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In this paper, a B-spline neural network (BNN) with a set of local basis functions is used to online approximate the unknown nonlinear system dynamics. The BNN has the advantage of locally controlling its network output compared with other neural networks; therefore, it is suitable to online estimate the unknown nonlinear system dynamics. Meanwhile, this paper proposes an adaptive B-spline neural...
This study proposes a growing-and-pruning adaptive RBF neural control (GP-ARBFNC) system for a class of uncertain nonlinear systems. The proposed GP-ARBFNC system is composed of a neural controller and a saturation compensator. The neural controller uses a growing-and-pruning RBF (GP-RBF) network to online mimic an ideal controller, and the saturation compensator is designed to dispel the approximation...
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...
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