Adaptive Identification and Application of Flow Mapping for Electrohydraulic Valves

Abstract

Good estimates of flow mapping for electrohydraulic valves are important in automation of fluid power system. The purpose of this paper is to propose adaptive identification methods based on a recursive least squares method (RLSM), a recursive maximum likelihood method (RMLM) and radial basis function neural network (RBFNN) to estimate the uncertain parameters in flow mapping for electrohydraulic valves. In order to reduce the complexity and improve the identification performance, model structures derived from prior knowledge are introduced. The methods are applied to map the pressure-flow characteristic of an electrohydraulic valve. With the help of simulation results, the accuracy and efficiency of these algorithms are demonstrated. Some issues like invertibility of flow mapping are discussed and suggestions to apply these methods are made.