Heat exchanger modeling using NARX model with binary PSO-based structure selection method

摘要

This paper explores the application of Non-Linear Autoregressive Model with Exogenous Inputs (NARX) system identification of heat exchanger system. Model structure selection was performed using the Binary Particle Swarm Optimization (BPSO) algorithm. The application of BPSO for model structure selection represents each particle's position as binary values, which were used to select a set of regressors from the regressor matrix. Parameter estimation was then performed using Householder-based QR factorization method. Tests performed on the heat exchanger system defined the model with a maximum lag of five, while fulfilling all model validation criterions.