Models of the anaerobic digestion process which predict digester behaviour sufficiently accurately could be used in process control. Although the process is generally considered to be non-linear, it could possibly be represented by an adaptive linear model, where the model adapts rapidly enough to represent the process at differing operating conditions and times in its operating life. Simple linear black box models of low order were investigated, predicting over a limited horizon and relying on current and recent data values to refine the prediction. Independent black box ARX models were identified for gas production rate, % CO2, bicarbonate alkalinity and Total Organic Carbon using on-line data from a fluidised bed reactor at varying organic load. Model predictions looked ahead one sample step (30 minutes) and when validated using data obtained in a different time period (separated by 4-8 weeks) gave significant predictions in each case. All the models consisted of only second or third order polynomials. The non-linear nature of the process was found to have little effect over the operating conditions investigated. Also the variation of the process within a 4-8 week period was not sufficient to cause the models to predict badly.

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