Neutralize the pH of wastewater using intelligent controllers for industrial reuse

Abstract

Water waste management is one of the significant hassles which is faced by the majority of industries. The industries let the wastewater into flowing streams or rivers near them, polluting the water resources in that locality. To prevent and safeguard the water resources, the government has given many regulations on the water quality before draining into the water sources. One of the primary problems is the amount of pH in the wastewater. The pH is a highly nonlinear quality of the liquids, as a single drop may change the quality to either acidic or alkaline. This paper proposes various intelligent controllers to maintain the wastewater's pH. The Nonlinear Autoregressive with External Controller (NARX) and Nonlinear Autoregressive (NAR) under deep neural network where the NARX model is synthesized based on two different algorithms which involve the Levenberg Marquardt (LM) and Scaled Conjugate Gradient (SCG) for maintaining pH. The controllers are being implemented on the pilot plant's process tank to determine and neutralize the pH. The pilot plant is interfaced MATLAB R2019b with the computer as a controller where the controller action for the neutralization is processed. The proposed NAR model did produce better results than the other models, whose settling times were 8.6 seconds and 0.5% overshoot. Furthermore, the NAR model has better results when compared with the other two neural models.