Adaptive identification and control algorithms for nonlinear bacterial growth systems. (English) Zbl 0544.93043

Dochain, D.; Bastin, G.

Automatica 20, 621-634 (1984).

Summary: This paper suggests how nonlinear adaptive control of nonlinear bacterial growth systems could be performed. The process is desribed by a time- varying nonlinear model obtained from material balance equations. Two different control problems are considered: substrate concentration control and production rate control. For each of these cases, an adaptive minimum variance control algorithm is proposed and its effectiveness is shown by simulation experiments. A theoretical proof of convergence of the substrate control algorithm is given. A further advantage of the nonlinear approach of this paper is that the identified parameters (namely the growth rate and a yield coefficient) have a clear physical meaning and can give, in real time, a useful information on the state of the biomass.

MSC:

93C40	Adaptive control/observation systems
92Cxx	Physiological, cellular and medical topics
93C10	Nonlinear systems in control theory
93E10	Estimation and detection in stochastic control theory
93E12	Identification in stochastic control theory
93E25	Computational methods in stochastic control (MSC2010)

Keywords:

nonlinear adaptive control; bacterial growth systems; adaptive minimum variance control algorithm

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