Robust multivariable control of complex biological processes |
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Authors: | T T Lee F Y Wang R B Newell |
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Affiliation: | a Institute of High Performance Computing, 1 Science Park Road # 01-01 The Capricorn Singapore Science Park II, Singapore 117528, Singapore;b Computer-Aided Process Engineering Centre, Department of Chemical Engineering, The University of Queensland, St. Lucia 4072, Brisbane, Qld, Australia |
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Abstract: | This paper addresses advanced control of a biological nutrient removal (BNR) activated sludge process. Based on a previously validated distributed parameter model of the BNR activated sludge process, we present robust multivariable controller designs for the process, involving loop shaping of plant model, robust stability and performance analyses. Results from three design case studies showed that a multivariable controller with stability margins of 0.163, 0.492 and 1.062 measured by the normalised coprime factor, multiplicative and additive uncertainties respectively give the best results for meeting performance robustness specifications. The controller robustly stabilises effluent nutrients in the presence of uncertainties with the behaviour of phosphorus accumulating organisms as well as to effectively attenuate major disturbances introduced as step changes. This study also shows that performance of the multivariable robust controller is superior to multi-loops SISO PI controllers for regulating the BNR activated sludge process in terms of robust stability and performance and controlling the process using inlet feed flowrate is infeasible. |
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Keywords: | Robust multivariable controller design BNR activated sludge process Reduced-order model Stability margins Uncertainty modelling |
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