Self Tuning from Noisy Response for Temperature Controller

Abstract

This paper presents a self tuning strategy from noisy response data for a temperature controller. A general pre-filtering procedure in modeling and identification from noisy response data is not required in the proposed method for a general purpose controller. A two-step procedure for the regulator design is proposed. Laplace transfer function model from noisy step response data is built based on the Laguerre functions and thier orthonomal proparties. Then a regulator is directly computed based on the dominant parameters of estimated transfer function. The sequential self tuning is quite simple. An experiment shows that the proposed method could be successfully and also be easily applied in practice.