Simulation of fluid power circuits using artificial network models: Part 1: Selection of component models

Abstract

Consideration is given to the transient analysis of fluid power circuits based solely upon a variety of artificial networks rather than the conventional mathematical modelling approach. Networks, trained using data from practical tests, are developed for an axial piston pump and filter, a proportional pressure relief valve, a lumped volume and a subsystem containing a proportional flow control valve driving an axial piston motor with its integral load assembly. A variety of networks are considered ranging from the linear-regression type, BARMAX, the self-organizing group method of data handling (GMDH) using nonlinear regression theory to multilayer perceptron (MLP) networks by the back propagation algorithm. Part 2 (1) then shows how the network models may be linked with the aid of additional steady state network models to predict the behaviour of a motor speed control system.