Universiti Teknologi Malaysia Institutional Repository

Data-driven adaptive model-based predictive control with application in wastewater systems

Abd. Wahab, Norhaliza and Katebi, R. and Balderud, J. and Rahmat, M. F. (2011) Data-driven adaptive model-based predictive control with application in wastewater systems. IET Control Theory and Applications, 5 (6). pp. 803-812. ISSN 1751-8644

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Abstract

This study is concerned with the development of a new data-driven adaptive model-based predictive controller (MBPC) with input constraints. The proposed methods employ subspace identification technique and a singular value decomposition (SVD)-based optimisation strategy to formulate the control algorithm and incorporate the input constraints. Both direct adaptive model-based predictive controller (DAMBPC) and indirect adaptive model-based predictive controller (IAMBPC) are considered. In DAMBPC, the direct identification of controller parameters is desired to reduce the design effort and computational load while the IAMBPC involves a two-stage process of model identification and controller design. The former method only requires a single QR decomposition for obtaining the controller parameters and uses a receding horizon approach to process input / output data for the identification. A suboptimal SVD-based optimisation technique is proposed to incorporate the input constraints. The proposed techniques are implemented and tested on a fourth order non- linear model of a wastewater system. Simulation results are presented to compare the direct and indirect adaptive methods and to demonstrate the performance of the proposed algorithms

Item Type:Article
Uncontrolled Keywords:wastewater systems, predictive control
Subjects:T Technology > TD Environmental technology. Sanitary engineering
Divisions:Electrical Engineering
ID Code:44832
Deposited By: Pn Haliza Zainal
Deposited On:21 Apr 2015 03:31
Last Modified:31 Jan 2017 06:21

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