Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment : a review

Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes.The authors acknowledge the financial support to the project PTDC/EBB-EBI/103147/2008 and the grant SFRH/BPD/48962/2008 provided by Fundacao para a Ciencia e Tecnologia (Portugal)

Feedback stabilization of fed-batch bioreactors: Non-monotonic growth kinetics

This paper deals with the design of a feedback controller for fed-batch microbial conversion processes that forces the substrate concentration C-S to a desired setpoint C-S*, starting from an arbitrary (initial) substrate concentration when non-monotonic growth kinetics apply. This problem is representative for a lot of industrial fermentation processes, with the baker's yeast fermentation as a well-known example. It is assumed that the specific growth rate mu is function of the substrate concentration only. A first approach exploits the availability of on-line measurements of both the substrate and biomass concentration. A second approach is merely based on on-line measurements of the biomass concentration, which provide an estimate for the specific growth rate. After a reformulation of the substrate concentration setpoint into a specific growth rate setpoint, it is demonstrated that the fed-batch process can still be stabilized around any desired operating point along the non-monotonic kinetics

Optimal temperature control of a steady-state exothermic plug-flow reactor

Optimal heat exchanger temperature profiles of exothermic tubular reactors were determined under the assumption of steady-state and plug-flow characteristics. The minimum principle of Pontryagin (optimal control theory) was applied in a straightforward analytical sense. To enable a trade-off between process performance and heat loss, a combined cost criterion was defined. In the first approach of specifying only, terminal costs, the optimal control input was of the bang-bang type that keeps the heat exchanger temperature constant at its maximum or minimum value. Afterwards, the terminal cost criterion was extended with an integral part that accounts for the global heat loss during the process. This integral cost part induced a control of the bang-singular-bang type. The desired performance call be met by selecting appropriate weights for terminal and integral costs

Optimal adaptive control of (bio)chemical reactors: past, present and future

In this paper an overview of optimal adaptive control of (bio)chemical reactors is presented. Following the paradigm of the Minimum Principle of Pontryagin the derivation of optimal control sequences for fed-batch production processes is briefly revisited. Next. it is illustrated how the obtained optimal profiles can be exploited in the characterization of nearly optimal control sequences in terms of the qualitative behavior of the specific growth and production rates as function of the limiting substrates. Implementing this knowledge leads in a natural way to the design of (nearly) optimal adaptive feedback controllers. Special emphasis will lie on the potential of on-line biomass measurements (obtained with the Biomass Monitor) in the estimation algorithm of the growth kinetics being the adaptive component of the controller. Extensions towards fermentation processes with (i) multiple substrates and (ii) non-monotonic kinetics are also included. Finally, perspectives towards optimal adaptive control of not perfectly mixed (bio)chemical reactor systems, such as chemical tubular reactors, are outlined. (C) 2004 Elsevier Ltd. All rights reserved