Black and Gray-Box Identification of a Hydraulic Pumping System

Abstract

The use of auxiliary information during the identifi- cation of nonlinear systems can be handled in different ways and at different levels. In this brief, static information of a 15 kW hydraulic pumping system is used as a priori knowledge in the parameters estimation of polynomial models which are compared to polynomial and neural models obtained by black-box techniques. The aim is to find models with good performance in both transient and steady-state regimes. This brief presents a novel bi-objective problem that uses free-run simulation and a new decisionmaker. The optimization problem is solved using a genetic algorithm. Compared with other techniques, the proposed approach can lead to models with better dynamic and static performance.