Sliding mode control for a nonlinear phase-field system

In the present contribution the sliding mode control (SMC) problem for a phase-field model of Caginalp type is considered. First we prove the well-posedness and some regularity results for the phase-field type state systems modified by the state-feedback control laws. Then, we show that the chosen SMC laws force the system to reach within finite time the sliding manifold (that we chose in order that one of the physical variables or a combination of them remains constant in time). We study three different types of feedback control laws: the first one appears in the internal energy balance and forces a linear combination of the temperature and the phase to reach a given (space dependent) value, while the second and third ones are added in the phase relation and lead the phase onto a prescribed target. While the control law is non-local in space for the first two problems, it is local in the third one, i.e., its value at any point and any time just depends on the value of the state.Comment: Key words: phase field system, nonlinear boundary value problems, phase transition, sliding mode control, state-feedback control la

Instrumentation and control of anaerobic digestion processes: a review and some research challenges

The final publication is available at Springer via http://dx.doi.org/10.1007/s11157-015-9382-6[EN] To enhance energy production from methane or resource recovery from digestate, anaerobic digestion processes require advanced instrumentation and control tools. Over the years, research on these topics has evolved and followed the main fields of application of anaerobic digestion processes: from municipal sewage sludge to liquid mainly industrial then municipal organic fraction of solid waste and agricultural residues. Time constants of the processes have also changed with respect to the treated waste from minutes or hours to weeks or months. Since fast closed loop control is needed for short time constant processes, human operator is now included in the loop when taking decisions to optimize anaerobic digestion plants dealing with complex solid waste over a long retention time. Control objectives have also moved from the regulation of key variables measured online to the prediction of overall process perfor- mance based on global off-line measurements to optimize the feeding of the processes. Additionally, the need for more accurate prediction of methane production and organic matter biodegradation has impacted the complexity of instrumentation and should include a more detailed characterization of the waste (e.g., biochemical fractions like proteins, lipids and carbohydrates)andtheirbioaccessibility andbiodegradability characteristics. However, even if in the literature several methodologies have been developed to determine biodegradability based on organic matter characterization, only a few papers deal with bioaccessibility assessment. In this review, we emphasize the high potential of some promising techniques, such as spectral analysis, and we discuss issues that could appear in the near future concerning control of AD processes.The authors acknowledge the financial support of INRA (the French National Institute for Agricultural Research), the French National Research Agency (ANR) for the "Phycover" project (project ANR-14-CE04-0011) and ADEME for Inter-laboratory assay financial support.Jimenez, J.; Latrille, E.; Harmand, J.; Robles Martínez, Á.; Ferrer Polo, J.; Gaida, D.; Wolf, C.... (2015). Instrumentation and control of anaerobic digestion processes: a review and some research challenges. Reviews in Environmental Science and Biotechnology. 14(4):615-648. doi:10.1007/s11157-015-9382-6S615648144Aceves-Lara CA, Latrille E, Steyer JP (2010) Optimal control of hydrogen production in a continuous anaerobic fermentation bioreactor. 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Dynamic grid adaptation applied to large eddy simulation turbulence modelling

At present a large number of fluid dynamics applications are found in aerospace, civil and automotive engineering, as well as medical related fields. In many applications the flow field is turbulent and the computational modelling of such flows remains a difficult task. To resolve all turbulent flow phenomena for flow problems where turbulence is of key interest is a priori not feasible in a Computational Fluid Dynamics (CFD) investigation with a conventional mesh. The use of a Dynamic Grid Adaptation (DGA) algorithm in a turbulent unsteady flow field is an appealing technique which can reduce the computational costs of a CFD investigation. A refinement of the numerical domain with a DGA algorithm requires reliable criteria for mesh refinement which reflect the complex flow processes. At present not much work has been done to obtain reliable refinement criteria for turbulent unsteady flow. The purpose of the work presented in this thesis is to use both a DGA algorithm and Large Eddy Simulation (LES) turbulence model for predicting turbulent unsteady flow. The criteria for mesh refinement used in this work are derived from the equation for turbulent viscosity in the LES turbulence model. By using a modification to the turbulent viscosity as a refinement variable there is a link between both DGA algorithm and turbulence model. The smaller scale turbulence is modelled via the LES turbulence model, while the larger scales are resolved. In comparison with the simulations using a conventional mesh, substantial reduction in mesh size has been obtained with the use of a DGA algorithm. The reduction in mesh size is obtained without a decay in the quality of the prediction. It is shown that the use of a DGA algorithm in the context of turbulence modelling is a suitable tool which can be used as a next step in an attempt to resolve turbulence more realistically

Process Control Applications in Microbial Fuel Cells(MFC)

abstract: Microbial fuel cells(MFC) use micro-organisms called anode-respiring bacteria(ARB) to convert chemical energy into electrical energy. This process can not only treat wastewater but can also produce useful byproduct hydrogen peroxide(H2O2). Process variables like anode potential and pH play important role in the MFC operation and the focus of this dissertation are pH and potential control problems. Most of the adaptive pH control solutions use signal-based-norms as cost functions, but their strong dependency on excitation signal properties makes them sensitive to noise, disturbances, and modeling errors. System-based-norm( H-infinity) cost functions provide a viable alternative for the adaptation as they are less susceptible to the signal properties. Two variants of adaptive pH control algorithms that use approximate H-infinity frequency loop-shaping (FLS) cost metrics are proposed in this dissertation. A pH neutralization process with high retention time is studied using lab scale experiments and the experimental setup is used as a basis to develop a first-principles model. The analysis of such a model shows that only the gain of the process varies significantly with operating conditions and with buffering capacity. Consequently, the adaptation of the controller gain (single parameter) is sufficient to compensate for the variation in process gain and the focus of the proposed algorithms is the adaptation of the PI controller gain. Computer simulations and lab-scale experiments are used to study tracking, disturbance rejection and adaptation performance of these algorithms under different excitation conditions. Results show the proposed algorithm produces optimum that is less dependent on the excitation as compared to a commonly used L2 cost function based algorithm and tracks set-points reasonably well under practical conditions. The proposed direct pH control algorithm is integrated with the combined activated sludge anaerobic digestion model (CASADM) of an MFC and it is shown pH control improves its performance. Analytical grade potentiostats are commonly used in MFC potential control, but, their high cost (>$6000) and large size, make them nonviable for the field usage. This dissertation proposes an alternate low-cost($200) portable potentiostat solution. This potentiostat is tested using a ferricyanide reactor and results show it produces performance close to an analytical grade potentiostat.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Design of nonlinear controllers through the virtual reference method and regularization

This work proposes a new extension for the nonlinear formulation of the data-driven control method known as the Nonlinear Virtual Reference Feedback Tuning. When the process to be controlled contains a significant quantity of noise, the standard Nonlinear VRFT approach – that uses the Least Squares method – yield estimates with poor statistical properties. These properties may lead the control system to undesirable closed loop performances and even instability. With the intention to improve these statistical properties and controller sparsity and hence, the system’s closed loop performance, this work proposes the use of ℓ1 regularization on the nonlinear formulation of the VRFT method. Regularization is a component that has been extensively employed and researched in the Machine Learning and System Identification communities lately. Furthermore, this technique is appropriate to reduce the variance in the estimates. A detailed analysis of the noise effect on the estimate is made for the Nonlinear VRFT method. Finally, three different regularization methods, the third one proposed in this work, are compared to the standard Nonlinear VRFT.Este trabalho propõe uma nova extensão para a formulação não linear do método de controle orientado por dados conhecido como Método da Referência Virtual Não Linear, ou Nonlinear Virtual Reference Feedback Tuning – denominado aqui somente como VRFT. Quando o processo a ser controlado contém uma quantidade significativa de ruído, a abordagem padrão do VRFT – que usa o método dos Mínimos Quadrados – fornece estimativas com propriedades estatísticas pobres. Essas propriedades podem levar o sistema de controle a desempenhos indesejáveis em malha fechada. Com a intenção de melhorar essas propriedades estatística, identificar um controlador simples em quantidade de parâmetros e melhorar o desempenho em malha fechada do sistema, este trabalho propõe o uso da regularização ℓ1 na formulação não linear do método VRFT. A regularização é uma técnica que tem sido amplamente empregada e pesquisada nas comunidades de Aprendizagem de Máquina e Identificação de Sistemas ultimamente. Além disso, esta técnica é apropriada para reduzir a variância das estimativas. Uma análise detalhada do efeito do ruído na estimativa é feita para o método VRFT não linear. Finalmente, três diferentes métodos de regularização, o terceiro proposto neste trabalho, são comparados com o VRFT