Adaptive control of dissolved oxygen concentration in a bioreactor

Abstract

A new adaptive DO (dissolved oxygen) concentration control algorithm considering DO electrode dynamics with response time delay has been developed. A system model with two time-varying parameters was used to relate the DO concentration with two control variables: air flow rate and agitation speed. Parameters of this model were estimated on-line using a regularized constant trace recursive least-squares method. An extended Kalman filter was used to remove the effect of noises from the DO concentration measurements and thus to improve control performance. A discrete one-step ahead control scheme was adopted to determine control actions based on the parameter estimation results. Experimental results showed that the new adaptive DO concentration control algorithm performed better than other algorithms tested, a PID controller and adaptive algorithms without the DO electrode dynamics.

Adaptive pole placement control algorithm for DO-control in β-lactamase production

“…A physical model of the gas absorption processes was used along with an estimator of the actual gas concentrations to account for the probe dynamics. Lee et al (1991) used a system model with two time-varying parameters to relate the dissolved oxygen concentration with two control variables: air flow rate and agitation speed. The parameters of this model were estimated on-line and used by a one-step ahead controller with a Kalman filter-based estimation of the real DO concentration in the bioreactor.…”

Set-point regulation of an anaerobic digestion process with bounded output feedback

“…Hence, consider the system composed of the subsystem of the system (9) with , and of the control law (10), i.e., (12) Choosing the candidate Lyapunov function (13) with , and 1 one gets (14) Set (15) and note that, for small and , one has for some . and the term in square bracket is positive.…”

“…This category includes, for example, the application of industrial controllers (such as PID or even on/off) within some simple control strategies such as the regulation of the pH into the reactor. Several linear feedback techniques, such as proportional and proportional-integral control [8], [9], [10] and adaptive control [11], [12], have been proposed. However, these approaches have the disadvantage of neglecting the nonlinearities inherent in most biological processes.…”

Control of dissolved oxygen concentration using neural network in a batch bioreactor

“…This effect is known as Crabtree effect [4]. Generally, a low DO concentration affects the catabolic pathways, the rate of microbial metabolism, and the product formation [14,15]. DO concentration control is a very difficult task, especially in batch fermentation because of time varying conditions, time delays and the probe dynamics.…”