Abstract
The paper deals with the problem of tracking control for a class of nonlinear systems in presence of the disturbances. The developed formation for the tracking control is taken into account as an adaptive neural sliding mode. A chattering phenomenon will be eliminated by reducing a norm of disturbance based on disturbance estimation and feed-forward correction. The set of controller’s parameter, which is a satisfy Hurwitz polynomial, is then updated by adaptive laws via a model reference system. In addition, the unknown nonlinear functions are estimated by radial basis functions neural network. The adaptive updated law based on radial basis functions neural network and a feed-forward correction is proposed to estimate both estimation errors of nonlinear functions and external disturbances, which is called lumped disturbances. An asymptotic stability of a closed loop system is illustrated by Lyapunov theory. And lastly, to demonstrate an efficiency of our approach, an illustrative example, a coupled-tank liquid system, is shown.
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Pham, T.V., Huy, D.D. (2018). Novel Adaptive Neural Sliding Mode Control for Uncertain Nonlinear System with Disturbance Estimation. In: Bhateja, V., Nguyen, B., Nguyen, N., Satapathy, S., Le, DN. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 672. Springer, Singapore. https://doi.org/10.1007/978-981-10-7512-4_14
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DOI: https://doi.org/10.1007/978-981-10-7512-4_14
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