Abstract
The application of control strategies in wastewater treatment plants has increased to improve their performance for treating influent. The fuzzy logic controller plays a vital role in this work and simulation work was carried out in a benchmark simulation model no.1 (BSM1) framework. The attempted work proposes two control schemes with the objectives of improving the effluent quality and minimizing the number of measurements taken from the plant. The design of fuzzy control schemes is based on five inputs and six outputs in order to accomplish the objectives. Experimental results show improvement in the effluent quality and increase in the efficacy of the control system. The proposed design is implemented using MATLAB with the adaptation in 2014a.
Highlights
Wastewater treatment includes numerous cycles and strategies which make a treatment plant with huge scale and complex framework
The plant is simulated with Proportional Integral (PI) controller and with the proposed fuzzy method
Some of the evaluation parameters considered for comparison are ammonia concentration, DO concentration and oxygen transfer coefficient in each aerobic reactor, effluent ammonia (SNH,e) concentration and total nitrogen (Ntot) concentration of the effluent
Summary
Wastewater treatment includes numerous cycles and strategies which make a treatment plant with huge scale and complex framework. Some wastewater treatment plant doesn’t have an anoxic tank separately; by cycling the air circulation blowers either to on or off condition, it might be expected to make an anoxic tank. This examines that cycling the blowers is done to decrease the power utilization. By all these concerns, the waste water treatments with fuzzy logic controllers on various applications are reviewed (Vijayaraghavan & Jayalakshmi 2015). Many aeration control schemes based on ammonia measurement were developed. Leiv Rieger discussed the case study on two control schemes based on ammonia measurement (Rieger et al 2014). I.Santin (Satin et al 2017) presented a cascade control strategy to minimize the nitrous oxide emissions and thereby maintaining a satisfactory trade-off between water quality and costs in Benchmark Simulation Model no. 2 Gas
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