Monitoring and control of an anaerobic upflow fixed‐bed reactor for high‐loading‐rate operation and rejection of disturbances

Abstract

A new control strategy has been introduced for operating anaerobic digestion processes efficiently at high load. The control system includes a cascade controller embedded into a rule-based supervisory system based on extremum-seeking control. Three process parameters, considered to be the most realistic variables for monitoring of the bioprocess, were selected (pH, biogas production rate, and the difference between the actual biogas flow and its setpoint). The control system examines these variables and varies the organic load by manipulating the influent flow. Good control performance was achieved during the start-up, during steady-state running operations, and during rejection of disturbances. The main advantages of this control approach can be attributed to its ability to adjust control parameters automatically, both for high-load operation and for rejection of disturbances. Furthermore, the influent flow can be tuned automatically according to variations in organic matter in the feed without the characteristics of the influent being considered.

Thermophilic anaerobic digester performance under different feed-loading frequency

“…For closer process monitoring and control, more frequent feedings would be desirable, especially with inconsistent or uncharacterized feedstocks. Digester pH, biogas production, and biogas composition change in response to changes in feed quality and quantity (13). The more frequent the feed input, the more opportunity the operator has to modify the volume or concentration of the feed to maintain steady-state conditions.…”

Multi-objective cascade controller for an anaerobic digester

“…2), which have different dynamic properties in terms of stability [50]. In practice, the risk of destabilisation of an AWT process can be avoided by operating in the stable region or far below the maximum reactor capacity (optimum methane flow rate production), i.e., K I · K S (K I is the inhibition kinetic constant and K S is half saturation constant) for the Haldane kinetic model [10].…”

“…This system allows the regulation of an anaerobic digester working at a low COD concentration. Liu et al [10,42,43] developed a cascade controller embedded into a fuzzy rule-based supervisory system. This approach demonstrated the ability to achieve high productivity conditions for the production of methane by the AWT reactor.…”

“…Most of the recently published work about expert systems for AWT control is based on fuzzy logic [23][24][25][26][27]. Moreover, fuzzy structures have been used to develop control systems from expertise of operators and phenomenological information [23,[28][29][30] to derive gainscheduling schemes for tuning on-line control parameters and to manage process uncertainties [10]. With this aim and due to the initial difficulty in modelling AWT systems, neural networks have been applied to develop controllers using data from AWT plants [13,31,32].…”

“…The aim of an anaerobic reactor controller is to maintain conditions of stability in a bioreactor against possible changes in influent characteristics (flow rate or composition) and to attain adequate effluent quality and maximise the methane productivity of the AWT plant [10]. Controllers can be designed for the management of the process under the following different operational scenarios: organic overload, hydraulic overload, toxic effects of inhibitor compounds, thermal shock and restart-ups [11].…”