Black and Gray-Box Identification of a Hydraulic Pumping System

作者：Barbosa Bruno H G^*; Aguirre Luis A; Martinez Carlos B; Braga Antonio P

来源：IEEE Transactions on Control Systems Technology, 2011, 19(2): 398-406.

DOI：10.1109/TCST.2010.2042600

• Genetic algorithms
• gray-box
• hydraulic system
• identification
• multi-objective
• nonlinear autoregressive with moving average and exogenous variables (NARMAX)
• simulation error
• static function

The use of auxiliary information during the identification 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 decision-maker. 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.

• 出版日期2011-3