Tube-based robust nonlinear model predictive control of anaerobic co-digestion

TL;DR

This paper proposes a tube-based robust nonlinear model predictive control approach to optimize bio-methane production in anaerobic co-digesters, effectively handling uncertainties and limited instrumentation through simulation-based validation.

Contribution

It introduces a novel tube-based robust NMPC method tailored for anaerobic co-digestion, addressing model uncertainties and operational constraints in full-scale plants.

Findings

Successful simulation of NMPC in mimicking experimental setup

Demonstrated robustness against model uncertainties

Potential for real-world application in pilot-scale plants

Abstract

To match the growing demand for bio-methane production, anaerobic digesters need to embrace the co-digestion of different feedstocks; in addition, to improve the techno-economic performance, an optimal and time-varying adaptation of the input diet is required. These operation modes constitute a very hard challenge for the limited instrumentation and control equipment typically installed aboard full-scale plants. A model-based predictive approach may be able to handle such control problem, but the identification of reliable predictive models is limited by the low information content typical of the data available from full-scale plants' operations, which entail high parametric uncertainty. In this work, the application of a tube-based robust nonlinear model predictive control (NMPC) is proposed to regulate bio-methane production over a period of diet change in time, while warranting safe operation and dealing with uncertainties. In view of its upcoming validation on a true small pilot-scale plant, the NMPC capabilities are assessed via numerical simulations designed to resemble as much as possible the experimental setup, along with some practical final considerations.