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Ramon Vilanova
Universitat Autònoma de Barcelona
Electrical & Electronics Engineering

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Data-driven adaptive predictive control for an activated sludge process Mashitah C. Razali; Norhaliza Abdul Wahab; Syahira Ibrahim; Azavitra Zainal; M. F. Rahmat; Ramon Vilanova
Bulletin of Electrical Engineering and Informatics Vol 9, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i5.2257

Abstract

Data-driven control requires no information of the mathematical model of the controlled process. This paper proposes the direct identification of controller parameters of activated sludge process. This class of data-driven control calculates the predictive controller parameters directly using subspace identification technique. By updating input-output data using receding window mechanism, the adaptive strategy can be achieved. The robustness test and stability analysis of direct adaptive model predictive control are discussed to realize the effectiveness of this adaptive control scheme. The applicability of the controller algorithm to adapt into varying kinetic parameters and operating conditions is evaluated. Simulation results show that by a proper and effective excitation of direct identification of controller parameters, the convergence and stability of the implicit predictive model can be achieved.
Co-Authors Azavitra Zainal M. F. Rahmat Mashitah C. Razali Norhaliza Abdul Wahab Syahira Ibrahim