On-line monitoring, state and parameter estimation, adaptive/computer control and dynamic optimization of a continuous bioreactor

In this research program, various important aspects for computer-based adaptive control and optimization strategy for a continuous bioreactor, have been investigated. The study was carried out in the following four phases: (a) development of a new method for on-line monitoring of biomass concentration; (b) measurement of kinetics of growth of S. cerevisiae; (c) dynamic bioreactor simulation studies; and (d) experimental control of a continuous bioreactor.; An interesting observation was made in absorption of light by yeast cells at "high" concentrations leading to a new equation: log (T/T{dollar}sb0{dollar}) = K log (C/C{dollar}sb0{dollar}), while developing a suitable method for on-line monitoring of yeast cell concentrations. A consistent theoretical explanation was developed starting from the fundamental assumptions of Beer-Lambert's law. This equation was shown to be valid for several optically sensitive solutions (with negative deviations) and thus has the potential of becoming a law. The underlying reasoning behind this phenomenon may improve our present day understanding about absorption of electromagnetic radiation by various substances.; Based on this new concept, a novel spectrophotometric technique has been developed and successfully implemented for on-line monitoring of a wide range of yeast cell concentrations in a continuous bioreactor (which has been considered a difficult task in the literature due to lack of reliable instrumentation). To the author's knowledge, this is the first successful method for on-line monitoring of "high" biomass concentrations which could be implemented for process control applications. This approach may lead to a new generation of instruments in spectroscopy.; Extensive batch and continuous experiments were carried out on a well-defined medium using S. cerevisiae at different initial glucose concentrations. The biomass yield was found to be a function of the inhibitory environment of the bioreactor. Four new correlations have been proposed to explain the inhibitory kinetics of ethanol fermentation. These experimental results are expected to have a significant influence in formulating the fermenter design variables and control strategy for optimizing the productivity of ethanol fermentation process.; Based on extensive simulation studies, an algorithm (called the SE algorithm) was successfully formulated using state equations: (a) for on-line estimation of important unmeasurable states and critical time-varying parameters; and (b) for adaptive control and dynamic optimization of a bioprocess. Based on simulation studies, a numerical technique was also developed to improve the convergence of the extended Kalman filter algorithm.; The SE algorithm was implemented for on-line state estimation and dynamic optimization of a lab-scale (450 mL working volume) continuous ethanol fermenter. An IBM PC along with an OPTO board were used for on-line data acquisition and for execution of the optimization algorithm. A number of experiments were carried out to verify the performance and true adaptive nature of the algorithm. The experimental results clearly illustrate the successful development and implementation of computer-based adaptive control and dynamic optimization strategies to a continuous bioprocess.