Dynamic Relative Gain Array Estimation using Local Polynomial Approximation Approach

Abstract

This article presents a procedure that utilizes the local polynomial approximation approach in the estimation of the Dynamic Relative Gain Array (DRGA) matrix and its uncertainty bounds for weakly nonlinear systems. This procedure offers enhanced frequency resolution and noise reduction when random excitation is used. It also allows separation of nonlinear distortions with shorter measuring time when multisine excitation is imposed. The procedure is illustrated using the well-known quadruple tank process as a case study in simulation and in real life. Besides, a comparison with the pairing results of the static RGA, nonlinear RGA and DRGA based on linearized quadruple tank model for different simulation cases is performed.

Decentralized robust evolving cloud-based controller for two input two output systems

“…The below is from the guidelines to be adopted for input-output pairs (Luyben, 1999; Kadhim et al, 2016; Seborg and Edgar, 2011):…”