In this paper, a comparison of linear and nonlinear estimators with particular emphasis to the closed-loop properties of the resulting inferential control scheme is presented. The concept of closed-loop “consistency” is introduced as an effective criterion for choosing the auxiliary variables. An estimator is consistent if it guarantees low closed- loop steady-state offset in the true unmeasured controlled variables. By means of a case study of a high purity distillation column, a number of issues that can arise in inferential control are emphasized, and their implications on the closed-loop stability are discussed. It is shown that the use of nonlinear estimators, which in general guarantee a superior precision, may be inappropriate because of the presence of zero gains and gain inversions that can lead the closed-loop system to instability. Moreover, in multi-input multi-output (MIMO) systems it is possible that the estimator requires the auxiliary variables to reach values that are not reachable by the actual plant. Copyright 2004 IFAC
A critical comparison of linear and nonlinear property estimators in inferential control
PANNOCCHIA, GABRIELE;BRAMBILLA, ALESSANDRO
2004-01-01
Abstract
In this paper, a comparison of linear and nonlinear estimators with particular emphasis to the closed-loop properties of the resulting inferential control scheme is presented. The concept of closed-loop “consistency” is introduced as an effective criterion for choosing the auxiliary variables. An estimator is consistent if it guarantees low closed- loop steady-state offset in the true unmeasured controlled variables. By means of a case study of a high purity distillation column, a number of issues that can arise in inferential control are emphasized, and their implications on the closed-loop stability are discussed. It is shown that the use of nonlinear estimators, which in general guarantee a superior precision, may be inappropriate because of the presence of zero gains and gain inversions that can lead the closed-loop system to instability. Moreover, in multi-input multi-output (MIMO) systems it is possible that the estimator requires the auxiliary variables to reach values that are not reachable by the actual plant. Copyright 2004 IFACI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
