Control of activated sludge treatment process using pre-compensated multi-variable quantitative feedback theory-based controller. (January 2022)

• Record Type: Journal Article
• Authors: Chakravarty, Sandipan Prasad; Roy, Aniket; Roy, Prasanta
• Is Part Of: Transactions of the Institute of Measurement and Control. Volume 44:Number 2(2022)
• Page Start: 506
• Page End: 522
• Publication Date: 2022-01
• Subjects: Waste water treatment plant (WWTP) -- activated sludge treatment process (ASTP) -- quantitative feedback theory (QFT); Automatic control -- Periodicals; Measuring instruments -- Periodicals; Commande automatique -- Périodiques; Mesure -- Instruments -- Périodiques; 681.2
• DOI: 10.1177/01423312211039048
• Languages: English
• ISSNs: 0142-3312

Abstract

This paper deals with the design of a pre-compensated multi-variable quantitative feedback theory (QFT)-based fully populated matrix controller for an activated sludge treatment process (ASTP) of a waste water treatment plant (WWTP). The regulation of the concentration of biochemical oxygen demand (BO D 5 ) and ammonium-ion (NH 4 + ) is the control objective. The plant dynamics are obtained using physical laws available in the literature. The parametric uncertainty is quantified from the measurement data obtained from a real ASTP of an oil refinery. The model is duly cross-validated. A novel technique is proposed to design a pre-compensator that will enhance the diagonal dominance of the plant transfer function matrix. A diagonal controller and a pre-filter, are then designed using a sequential multi-input multi-output (MIMO) QFT-based methodology to meet a set of performance specifications such as relative stability, disturbance rejection, robust tracking and so forth. The simulation results validate the effectiveness of the proposed control scheme. A comparative analysis with reported works shows that the proposed control scheme outperforms some of the reported control strategies.