State estimation of the time–space propagation of COVID-19 using a distributed parameter observer based on a SEIR-type model

The real-time prediction and estimation of the spread of diseases, such as COVID-19 is of paramount importance as evidenced by the recent pandemic. This work is concerned with the distributed parameter estimation of the time–space propagation of such diseases using a diffusion–reaction epidemiological model of the susceptible–exposed–infected–recovered (SEIR) type. State estimation is based on continuous measurements of the number of infections and deaths per unit of time and of the host spatial domain. The observer design method is based on positive definite matrices to parameterize a class of Lyapunov functionals, in order to stabilize the estimation error dynamics. Thus, the stability conditions can be expressed as a set of matrix inequality constraints which can be solved numerically using sum of squares (SOS) and standard semi-definite programming (SDP) tools. The observer performance is analyzed based on a simplified case study corresponding to the situation in France in March 2020 and shows promising results.Campus At

Observer design for multivariable transport-reaction systems based on spatially distributed measurements

This paper is concerned with the design of observers for a class of one-dimensional multi-state transport-reaction systems considering distributed in-domain measurements over the spatial domain. A design based on the Lyapunov method is proposed for the stabilization of the estimation error dynamics. The approach uses positive definite matrices to parameterize a class of Lyapunov functionals that are positive in the Lebesgue space of integrable square functions. Thus, the stability conditions can be expressed as a set of LMI constraints which can be solved numerically using sum of squares (SOS) and standard semi-definite programming (SDP) tools. In order to evaluate the proposed methodology, a state observer is designed to estimate the variables of a nonisothermal tubular reactor model. Numerical simulations are presented to demonstrate the potentials of the proposed observer.Campus Arequip

Nonlinear Model Predictive Control of a Wastewater Treatment Process Fitted with a Submerged Membrane Bioreactor

International audienceSubmerged membrane bioreactors are increasingly applied for wastewater treamentbut requires a tight control of the membrane fouling so as to ensure safe and efficient operation.The objective of this paper is to design a nonlinear model predictive control to minimize theirreversible resistance while keeping the trans-membrane pressure, which is a good indicatorof membrane fouling, at an acceptable level. To this end, the manipulated variables are thepermeate flow and the air scouring flow, which allows the material layer formed on the membrane(in short the “cake”) to be detached. The NMPC structure is tested in simulation consideringa detailed simulator as the reference process, and a reduced-order model as the predictor. Theresults show that the process can be regulated until the irreversible resistance takes the mainrole in the fouling resistance. When this state is reached, a chemical cleaning is required, or alarger trans-membrane pressure has to be accommodated

Design, Analysis and Validation of a Simple Dynamic Model of a Submerged Membrane Bioreactor

International audienceIn this study, a simple dynamic model of a submerged Membrane BioReactor (sMBR) is proposed, which would be suitable for process control. The system dynamics is first analyzed showing the existence of three different time scales. The existence of slow-fast dynamics is central to the development of a dedicated parameter estimation procedure. The proposed model structure is validated using realistic simulation data from a detailed simulator built in a well-established environment, namely GPS-X. Finally, a nonlinear model predictive control is designed to illustrate the potential of the developed model within a model-based control structure. The problem of water treatment in a recirculating aquaculture system is considered as an application example

Optimización de la productividad del cultivo de microalgas basada en control predictivo

Existe un interés creciente en los cultivos de diversas especies de microalgas debido a sus potenciales aplicaciones. En este trabajo se presenta un esquema de control basado en modelo predictivo para maximizar la productividad de estos cultivos. El modelo empleado considera crecimiento sobre un substrato limitado y el proceso de foto-aclimatación, fenómenosclave para la obtención de resultados coherentes con el comportamiento de este sistema.Fil: Gorrini, Federico Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Biagiola, Silvina Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Vande Wouwer, Alain. Université de Mons; Bélgica27º Congreso Argentino de Control Automatico AADECA’20Buenos Aires (Virtual)ArgentinaAsociación Argentina de Control Automátic

Experimental study of substrate limitation and light acclimation in cultures of the microalgae Scenedesmus obliquus—Parameter identification and model predictive control

In this study, the parameters of a dynamic model of cultures of the microalgae Scenedesmus obliquus are estimated from datasets collected in batch photobioreactors operated with various initial conditions and light illumination conditions. Measurements of biomass, nitrogen quota, bulk substrate concentration, as well as chlorophyll concentration are achieved, which allow the determination of parameters with satisfactory confidence intervals and model cross-validation against independent data. The dynamic model is then used as a predictor in a nonlinear model predictive control strategy where the dilution rate and the incident light intensity are simultaneously manipulated in order to optimize the cumulated algal biomass production.Fil: Gorrini, Federico Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Lara, Jesús Miguel Zamudio. Université de Mons; Bélgica. Universidad de Guanajuato; MéxicoFil: Biagiola, Silvina Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; ArgentinaFil: Escoto, Héctor Hernández. Universidad de Guanajuato; MéxicoFil: Hantson, Anne Lise. Université de Mons; BélgicaFil: Wouwer, Alain Vande. Université de Mons; Bélgic

Some Considerations About Control of Multispecies Anaerobic Digestion Systems

info:eu-repo/semantics/publishe

Model Development for Phosphate Recovery from Acidic Wastewater

info:eu-repo/semantics/publishe

A constructive approach to assess the stability of anaerobic digestion systems

info:eu-repo/semantics/publishe

Model-Free Extremum Seeking Control of Bioprocesses: A Review with a Worked Example

Uncertainty is a common feature of biological systems, and model-free extremum-seeking control has proved a relevant approach to avoid the typical problems related to model-based optimization, e.g., time- and resource-consuming derivation and identification of dynamic models, and lack of robustness of optimal control. In this article, a review of the past and current trends in model-free extremum seeking is proposed with an emphasis on finding optimal operating conditions of bioprocesses. This review is illustrated with a simple simulation case study which allows a comparative evaluation of a few selected methods. Finally, some experimental case studies are discussed. As usual, practice lags behind theory, but recent developments confirm the applicability of the approach at the laboratory scale and are encouraging a transfer to industrial scale