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Neural networks (NNs) have numerous applications to online processes, but the problem of stability is rarely discussed. This is an extremely important issue because, if the stability of a solution is not guaranteed, the equipment that is being used can be damaged, which can also cause serious accidents. It is true that in some research papers this problem has been considered, but this concerns continuous-time...
This paper deals with the problem of delay-dependent exponential stability in the mean square for a class of uncertain stochastic systems with time-varying delay and nonlinearities. By using Lyapunov-Krosovskii functional method combined with linear matrix inequalities (LMIs) techniques, some new delay-dependent stability criteria in terms of LMIs are derived by introducing some free weighting matrices...
A B-spline neural-network-based variable structure controller (VSC) for a class of nonlinear systems with parameter uncertainties is presented. The neural networks compensator is used to compensate the uncertainties in the systems. The tracking performance and stability is guaranteed by the VSC controller. The asymptotical stability of overall systems is verified by the Lyapunov stability criterion...
A robust adaptive neural network control scheme is proposed for a class of strict-feedback nonlinear systems with unknown control directions and unmodeled dynamics. The proposed design method expands the class of nonlinear systems for which robust adaptive control approaches have been studied. A priori knowledge of the signs of the control directions is not required. It is proved that under the proposed...
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