Nonlinear State-Affine Identification Methods; Applications to Electrical Power Plants

Abstract

Nonlinear identification is of great importance in many engineering designs, to represent the dynamical behaviour of certain industrial processes for important disturbances.The nonlinear model using physical equations and adjustment by experimental measures is not easy and requires considerable computing time.In this paper, we propose new nonlinear identification algorithms based on the least squares method and the use of polynomial extension of bilinear systems. This representation keeps the practical characterizations such as gain and time constants and enables a valid model to be obtained over a large range of working conditions.Several practical applications concerning hydraulic, thermal and nuclear electrical power plants are given and illustrate the validity of this identification procedure.