EDUCATION: - M.Sc. in Chemistry (Industrial Chemistry). University of Vigo (Spain). 2001 - Ph.D. in Applied Mathematics. University of Vigo (Spain). 2008
KEYWORDS: Distributed systems, robust control, reduced order models, mathematical modelling, simulation, dissipative systems. Application to chemical and biological systems.
PREVIOUS POST-DOC: Automatic Control Laboratory (Université de Mons, Belgium). From May, 2008 till December 2009
Abstract: This work presents a methodology which exploits the underlying biochemical structure of bioprocesses to estimate concentrations in aerobic fermenters from oxygen measurements. Although a number of estimators have been proposed over the years in the literature, the methodology proposed in this work is able to operate in transient conditions while does not require the knowledge of the growth kinetics. In addition, it can be also applied to fermenters where the spatial distribution of the concentrations is relevant. In this case, we propose a systematic approach to optimally locate the sensors based on the use of reduced order models. This method allows the reconstruction of the oxygen concentrations from a limited number of sensors. Finally, the methodology proposed will be illustrated on a horizontal tubular reactor for the production of gluconic acid by free-growth of Aspergillus niger.
Abstract: In many cases, it is difficult to derive a precise mathematical model, based on first principles, for a given process. Besides, the computation of the solution of models obtained through this methodology may require a large computational effort making them useless for real time tasks like control or optimization. Neurofuzzy modelling, which permits an easy way to derive successful models, is a good alternative which can be employed to overcome such limitations. In this paper, together with the neurofuzzy modelling, several strategies based on non-linear predictive control are presented. The low computational cost associated with neurofuzzy models and controllers makes them suitable candidates to be implemented into industrial Programmable Logic Controllers (PLC). Both the model and controllers are validated and implemented in a pilot plant for the thermal sterilization of solid canned food in steam retorts and based on the results, a comparison between the different predictive control strategies is presented.
Abstract: This work presents the theoretical design and the experimental validation of a real time optimisation logic for distributed parameter systems. This logic consists of a hierarchy of two layers. The upper layer is responsible of obtaining the optimal control profile by a suitable combination of the control vector parameterisation approach with a hybrid globallocal optimiser and the use of reduced models for distributed parameter systems. The lower layer corresponds to a PID controller designed in the framework of Internal Model Control to keep tracking capabilities at short time scales. This logic was applied to the real time optimisation of the thermal processing of packaged foods in batch retorts at the pilot plant available at the IIM-CSIC. The objective was to maximise food product quality while satisfying safety constraints. The proposed scheme was able to optimally operate the system under standard plant perturbations and under a pressure drop.
Abstract: A novel chemical reactor, the Open Plate Reactor, is being develop by Alfa Laval AB. It combine good mixing with high heat transfer capacity. In this reactor highly exothermic reactions can be produced using more concentrated reactants. A nonlinear model predictive control is proposed to maximize the reaction yield under hard input and state constraints. A reduced order model is proposed to decrease the optimization time, so we can implement it online. The approach takes advantage of the use of global spatial basis functions and uses the proper orthogonal decomposition (POD), to approximate the system by a low-dimensional set of ordinaries di®erential equations (ODEs). Simulations show a high reaction yield and ensure that the temperature inside the reactor do not exceed the safety limit.
