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13 - Electrical and Electronic Engineering, Metallurgy and Materials

University of Birmingham : A - Electronic, Electrical and computer engineering

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Output 44 of 108 in the submission

Article title

Genetic Hybrid Predictive Controller for Optimized Dissolved-Oxygen Tracking at Lower Control Level

Type

D - Journal article

DOI

10.1109/TCST.2008.2004499

Title of journal

IEEE Transactions on Control Systems Technology

Article number

Volume number

Issue number

First page of article

1183

ISSN of journal

1063-6536

Year of publication

2009

URL

Number of additional authors

Additional information

A new hierarchical two-level controller for optimal input of oxygen in activated sludge processes is developed and validated on a real wastewater treatment plant at Tczew, northern Poland, achieving about 30% reduction of energy cost and decreased blower switching frequency. The lower level controller (LLC) controls the aeration system, which has complicated hybrid and heavily constrained nonlinear dynamics. This paper derives a superior nonlinear hybrid predictive control algorithm for the LLC. A novel genetic optimiser is derived with dedicated operators for the problem, allowing for efficient handling the air blower switching constraints. Work was within EU project SMAC.

Interdisciplinary

Cross-referral requested

Research group

C - Railway Research and Energy

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract