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This paper presents batch-to-batch iterative learning control (ILC) of a fed-batch fermentation process using batch-wise linearised models identified from process operation data. The newly obtained process operation data after each batch is added to the historical data base and an updated linearised model is adaptively identified. In an effort to adapt to the current process environment, the updated...
This paper presents an iterative learning control strategy for a fed-batch fermentation process using linearised models identified from process operational data. Off-line calculated control policies for batch fermentation processes may not be optimal when implemented on the processes due to model plant mismatches and/or the presence of unknown disturbances. In order to overcome the effect of model...
This paper addresses the multi-variable optimisation of bioreactor performance. The central idea here is to use a time series model, which is identified on-line, to evaluate the steady-state performance of the bioreactor. A simple algorithm has been developed around this theme and analysed in Kambhampati et al (1989). A fermentation process model has been developed to provide a test system for the...
It has long been thought that bioprocesses, with their inherent measurement difficulties and complex dynamics, posed almost insermountable problems to the control engineer. Although much research has recently been biased towards the development of biosensors to give more insight into process dynamics, this paper concentrates on more effective use of those measurements which are already available....
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