Djalel Mazouni

Dynamical modelling, identification and software sensors for SBRs

This paper presents the two models, called EM1 and EM2, obtained for the two process configurations considered within the EOLI project. It also gives results of software sensors based on these models to provide on-line estimates of unmeasured process variables, and for which the design has considered in particular uncertainty on the model parameters.

Experiments for modelling the biodegradation of wastewater in sequencing batch reactors

Three types of wastewater were considered: typical municipal wastewater and the effluent of a dairy industry, both polluted with organic carbon and nitrogen, and wastewater typical of a chemical industry, containing toxic or recalcitrant compounds (4-chlorophenol). Sequencing batch reactors (SBRs) were considered. Process experiments were performed to provide experimental data for parameter identification of the dynamical models of the SBRs. The processes were instrumented with sensors to measure O2, NH3, T, pH, OUR, and other off line measurements (e.g.: NO2 − and NO3 −, COD, phenol concentration, microbiological counts and activities) in order to study more accurately the behaviour of the biomasses. However, the general idea is to design a system with a minimal number of sensors.

A Simple Mass Balance Model for Biological Sequencing Batch Reactors Used for Carbon and Nitrogen Removal

Abstract This paper presents a very simple mass balance model structure for Sequencing Batch Reactors used for the biological treatment of organic carbon and nitrogen. This model is intended to be used for control purposes. As such, the degree of details required is not too high and only major biological processes are taken into account. This model is identified and validated with real data acquired on a real SBR pilot pant. Some conclusions and perspectives are then drawn.

Optimal control of biological SBRs for the treatment of dairy and toxic wastewaters

This paper presents two optimal control strategies developed for the control of two biological sequencing batch reactors (SBR), the first one performing both organic carbon and nitrogen removal from dairy wastewaters, while the second one treats toxic wastewaters. The proposed control laws are based on models that have been validated with real data acquired on two real biological SBR pilot plants. These models are presented in D. Mazouni et al., 16th IFAC World Congress, Prague, 5–8 July 2005. The validation results of these control strategies are presented and discussed.

A MULTI-MODEL APPROACH FOR THE MONITORING OF CARBON AND NITROGEN CONCENTRATIONS DURING THE AEROBIC PHASE OF A BIOLOGICAL SEQUENCING BATCH REACTOR

Abstract This paper presents i) an extension of a simple model describing the dynamical behavior of important variables during the aerobic phase of a biological wastewater treatment plant and ii) a simple asymptotic observer based on this extended model for online estimating both soluble biodegradable carbon and nitrate+nitrite nitrogen concentrations. The proposed model is identified and the observer is validated with real data acquired on a real biological Sequencing Batch Reactor pilot plant.

Development of hardware sensors for the online monitoring of SBR used for the treatment of industrial wastewaters

The main challenge in the management of a sequencing batch reactor, for the biological treatment of urban and industrial wastewaters, is to ensure stable treatment efficiency under highly variable influent quality and quantity. To cope with this challenge, online instrumentation is fundamental, since it allows to characterize both influent variability and process efficiency. The more the online data are closely correlated with influent quality and SBRs treatment capacity, the more straightforward is the implementation of control strategies based on these data. In this paper, two monitoring techniques are described, which allow to obtain influent-related and process-related data: set-point titration and UV spectrophotometry. Despite the very different measuring principles, both techniques were successfully applied to SBRs monitoring and control leading to comparable results.

ATTAINABILITY AND SUBOPTIMAL MINIMAL TIME CONTROL OF A CLASS OF BIOLOGICAL SEQUENCING BATCH REACTORS

Abstract In this paper, geometric tools are used for the attainability study of biological Sequencing Batch Reactors (SBR). It consisted in finding the set of initial conditions from which one can reach a final state target with admissible control. The possible solutions can be determined easily once the set of reachability is fixed. In the second step, optimal time control problem is considered. It consist in finding the switching instant between the different steps of the batch. Pontryagins Maximum principle is used to solve a part of this problem. We propose asuboptimal solution allowing at most two commutation. A new problem is considered where the criteria is parameterized by the switching concentrations. A numerical solution is then proposed to solve this new minimal time problem.

Development of an integrated system for the optimization of sequencing batch reactors

This paper presents (i) a synthesis of the EOLI supervision system for optimizing both the biological reaction phases and the settling phase of Sequencing Batch Reactors (SBR) performing carbon and nitrogen removal from urban or industrial wastewaters; (ii) a summary of the integration capabilities of the integrated system developed by an industrial partner of the project to propose both the hardware and the software of the EOLI solution under a unified framework.

Optimization of sequencing batch(bio)-reactors—Challenging issues

Abstract This paper discusses several theoretical as well as practical challenging issues related to a recently developed time-optimal control strategy for the optimization of oxic/anoxic Sequencing Batch Reactors (SBR) for the removal of organic carbon and nitrogen from urban and industrial wastewaters and to its practical implementation.