LNU-FUZZY NETWORK AS A MATHEMATICAL ADAPTIVE MODEL OF A HYDRAULIC SYSTEM

Abstract

Model adaptive controllers such as Model Predictive Control or Model Reference Adaptive Control need a precise mathematical model of the controlled system adaptable in real-time. Systems consisting of a hydraulic 4-way proportional valve and a linear motor have non-linear behaviour such as hysteresis of and valve, death zone of a valve spool, time delay of a data transfer and control unit, dependence on coils temperature and oil temperature and nonlinear flow characteristics. This paper introduces modified Neuro-Fuzzy network as a mathematical adaptive model of a hydraulic system with above mentioned properties. The paper presents the basic architecture of Neuro-Fuzzy network which consists of artificial neural units a fuzzy layer and introduces modifications focused on identification. The basic real-time learning method such as Normalized Gradient Descent is introduced specially for the designed Neuro-Fuzzy Network. Identification and real time learning abilities of the model were tested on the hydraulic stand.

Recommended articles

USAGE OF TOPOLOGICAL OPTIMIZATION IN DESIGN OF MECHANICAL FORGING PRESSES

KAREL RAZ, MILAN CECHURA
Keywords: mechanical press | topological optimization | deformation | weight | forging

EXPERIMENTAL TESTING OF STEEL WIRE ROPES

MARIANNA TOMASKOVA
Keywords: steel wire rope | mechanical tests | competence coefficient

HIGH PRESSURE HYDRAULICS IN DIESEL ENGINE FUEL SYSTEM

VACLAV VONDRACEK, MIROSLAV MALY, ZDENEK TROJAN
Keywords: fuel distribution | injection system | injector