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Control of a Waste Water Treatment Plant Using Fuzzy Logic Controller

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Abstract

Waste water is a contaminated water consisting of water and impurities. Many factors affect the treatment plants; these includes physical, chemical properties and biological properties. The conventional controllers are being used for the waste water treatment processes. In the present paper, benchmark simulation model (BSM) provided by Alex et al. [Benchmark Simulation Model No. 1 (BSM1). Industrial Electrical Engineering and Automation. Lund University, Prepared by the IWA Task group on Benchmarking of Control Strategies for WWTPs, (2008)] has been considered for the fuzzy logic control. BSM model consists of five reactors in series and one clarifier. It is described as multivariable and nonlinear process with 13 variables in each reactor. The first two reactors are of anaerobic, and next three reactors are of aerobic. The objective is to control the dissolved oxygen (DO) in the fifth reactor using KLa5, mass transfer coefficient, i.e., air flow rate as the manipulated variable. The present fuzzy logic controller (FLC) design is based on Mamdani, IF..THEN.. rules. The performance of Fuzzy logic controller has been evaluated using MATLAB and Simulink Tool box. The FLC has been found to be superior than conventional PID controller i) for various set point changes for dissolved oxygen (DO) control, ii) for disturbance in the fresh feed concentrations and iii) for disturbances in KLa3 of reactor 3 and KLa4 of reactor 4.

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Acknowledgements

This paper is a revised and expanded version of an article entitled, "Control of Waste Water Treatment Plant using Fuzzy Logic Controller" presented in '36th National Convention of Chemical Engineers' hosted by Durgapur Local Centre of The Institution of Engineers (India) held through online during March 6–7, 2021.

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The authors declare that no funds, grants, or other support were received for this work.

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Correspondence to Prabhaker Reddy Ginuga.

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Yelagandula, S., Ginuga, P. Control of a Waste Water Treatment Plant Using Fuzzy Logic Controller. J. Inst. Eng. India Ser. E 103, 167–177 (2022). https://doi.org/10.1007/s40034-022-00241-9

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  • DOI: https://doi.org/10.1007/s40034-022-00241-9

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