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Energy from biomass and waste is regarded as one of the most dominant future renewable energy sources to comply with a continuous power demand. In this context, anaerobic digestion (AD) is emerging in control engineering applications at a spectacular pace. The necessity for advanced control of AD systems is motivated by the challenges of the process in terms of instability problems, especially when applying high influent loads with variable composition. Intrinsic process advantages, such as efficiency in pollutant removal or energy production, can also be part of global process optimization through advanced control. The aim of this paper is to analyse the application of Extended Prediction Self-Adaptive Control (EPSAC), a model based predictive control strategy, to AD processes. The widely adopted Anaerobic Digestion Model No. 1 (ADM1) is used to simulate the AD process and to extract simplified models for prediction over a future time interval. The general control strategy objective is to manipulate the inputs within the operation limits such that maximum methane production is ensured.