Circular economy-based multi-objective decentralized controller for activated sludge wastewater treatment plant

Abstract

Introduction: Water scarcity and water pollution are two major issues in India. Circular economy-based wastewater treatment technology provides the most sustainable solutions for solving these issues. In this paper, a novel multi-objective decentralized controller (MODC) is proposed for benchmarking a multi-input multi-output (MIMO) activated sludge wastewater treatment plant (WWTP) to achieve maximum effluent quality with minimum cost. WWTPs with conventional control schemes consume more energy to achieve the desired effluent quality. Methods: In this study, a MIMO model is developed for the activated sludge process (ASP) from a physics-based model, and relative gain array (RGA) analysis are carried out to determine the interaction between the loops to identify a suitable control scheme for the MIMO process. In addition, a multi-objective decentralized control problem is formulated to achieve the conflicting multiple objectives of improving effluent quality and minimizing operational costs by efficient usage of energy. Results and discussion: The desired quality and cost reduction are verified by comparing the integral square error (ISE) and control effort (CE) values of a closed-loop WWTP. A multi-objective evolutionary algorithm (MOEA), namely, the non-dominated sorting genetic algorithm (NSGA)-II, successfully solves the multi-objective control problem. NSGA-II provides several optimal solutions in the Pareto front. In order to demonstrate the feasibility of the proposed controller, three optimal solutions are selected from the Pareto-optimal front, and their closed-loop performances are evaluated qualitatively and quantitatively for both servo and regulatory operations. Improving the quality of effluent enhances active sludge production, which in turn increases the methane production in the anaerobic digester.