Maximum likelihood adaptive observer for bioprocesses

A particularity of cell culture processes is the relatively restricted number of valuable and accurate measurements for process control. Software sensors are an interesting solution in response to this problem since it provides non measured state estimation combining the available measurements to a mathematical model. But, due to the complexity of cell culture processes, the mathematical model itself may present some uncertainties particularly in the kinetic description. Such a difficulty has lead to the development of adaptive observers which are designed to jointly estimate state variables and model parameters. However those observers may become particularly difficult to design and to tune as the process complexity increases. In this contribution, an adaptive observer based on the theory of the full horizon and the asymptotic observers is proposed and illustrated.