Identification of Industrial boiler furnace using Linear Parameter Varying model

Abstract

System or process identification is a mathematical modeling of systems (processes) from test or experimental data. Process models obtained from identification process can be used for operator training simulator, analysis and design of safety systems, and design of process and control systems. This paper presents the Linear Parameter Varying (LPV) model identification for Industrial boiler furnace. LPV model is the development of linear time invariant models of different operating conditions along the overall operating trajectory and interpolation of linear models. The LPV model is adopted by considering the fact that boiler furnace in the thermal power plant has several operating conditions. By assuming that on every operating condition there are parameters changes, the LPV model is suitable for covering all operating conditions. The boiler furnace is modeled as LPV systems with Linear transfer function model structure. Identification algorithm used in the identification process is Prediction error method. Data needed for identification is taken from first principle model of the process with sampling time of 1 second. The identification result is simulated and validated with the measured data. The simulation result shows better accuracy for Linear Parameter Varying model.