A model-based framework for controlling activated sludge plants

TL;DR

This paper introduces a flexible, model-based control framework for activated sludge plants, utilizing a customisable Output Model-Predictive Controller to optimize wastewater treatment and resource recovery.

Contribution

It presents a novel, adaptable control framework combining state estimation and predictive control tailored for activated sludge plants.

Findings

Effective control of ASPs for wastewater treatment and nitrogen content regulation.

Framework adapts to technological and operational constraints.

Demonstrated potential for energy recovery and compliance with norms.

Abstract

This work presents a general framework for the advanced control of a common class of activated sludge plants (ASPs). Based on a dynamic model of the process and plant sensors and actuators, we design and configure a highly customisable Output Model-Predictive Controller (Output MPC) for the flexible operation of ASPs as water resource recovery facilities. The controller consists of a i) Moving-Horizon Estimator for determining the state of the process, from plant measurements, and ii) a Model-Predictive Controller for determining the optimal actions to attain high-level operational goals. The Output MPC can be configured to satisfy the technological limits of the plant equipment, as well as operational desiderata defined by plant personnel. We consider exemplary problems and show that the framework is able to control ASPs for tasks of practical relevance, ranging from wastewater treatment subject to normative limits, to the production of an effluent with varying nitrogen content, and energy recovery.