Quasi-Sliding Mode Control With Orthogonal Endocrine Neural Network-Based Estimator Applied in Anti-Lock Braking System

This paper presents a new control method for nonlinear discrete-time systems, described by an input-output model which is based on a combination of quasi-sliding mode and neural networks. First, an input-output discrete-time quasi-sliding mode control with inserted digital integrator, which addition...

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Veröffentlicht in:	IEEE/ASME transactions on mechatronics 2016-04, Vol.21 (2), p.754-764
Hauptverfasser:	Peric, Stanisa Lj, Antic, Dragan S., Milovanovic, Miroslav B., Mitic, Darko B., Milojkovic, Marko T., Nikolic, Sasa S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Adaptive neuro-fuzzy inference system anti-lock braking system Automotive engineering Biological neural networks Braking systems Computer simulation Dynamical systems endocrine neural networks estimation of modeling error Mathematical models Mechatronics Modelling Neural networks Neurons Nonlinearity orthogonal functions Polynomials sliding mode control Uncertainty
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