In-situ bioremediation for petroleum contamination: A fuzzy rule-based model predictive control system

The in-situ bioremediation process is widely adopted for treating petroleum contaminated sites. The objective of this paper is to propose a hybrid fuzzy rule-based model predictive process control system, which supports automated and real-time control of the in-situ bioremediation process while optimizing its inherently complex physical, chemical, and biological processes. This control system can identify the optimal control action sequence and its corresponding trajectory of process outputs, while at the same time minimizing the total operation cost of the process. The proposed control system improves upon earlier versions of the process control system because it can handle in real-time the unavoidable imprecision of the bioremediation simulation model and the uncertainty implicit in the fuzzy control rules developed based on a survey questionnaire.