State Variables Estimation for a Counter-Flow Double-Pipe Heat Exchanger Using Multi-linear Model

This paper deals with the state variables (temperatures) estimation for a counter-flow double-pipe heat exchanger using multi-linear models using a Kalman filter (FK) for the state variables approaching and using Bayes probability for the change of the model. The reliability of the proposed method was demonstrated via numerical simulation and laboratory experiments with a bench-scale pilot plant.