Дисертації з теми "Process control Dynamics Mathematical models"

Orientadores: Rubens Maciel Filho, Delba Nisi Cosme Melo
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química
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Resumo: Esta pesquisa teve por finalidade o desenvolvimento de uma metodologia de otimização em duas camadas. A otimização preliminar foi baseada na técnica de planejamento de experimentos junto com a metodologia por superfície de resposta com a finalidade de identificar uma possível região de busca do ponto de operação ótimo, o qual foi obtido através da implementação de métodos híbridos de otimização desenvolvidos mediante associação do modelo determinístico de otimização por programação quadrática sucessiva (SQP) com a técnica dos algoritmos genéticos (GA) no modelo do processo de craqueamento catalítico fluidizado- FCC. Este processo é caracterizado por ser um sistema heterogêneo e não isotérmico, cuja modelagem detalhada engloba as equações de balanço de massa e energia das partículas do catalisador, como também para a fase líquida e gasosa, sendo um dos casos de estudo para a aplicação da metodologia de otimização desenvolvida. Como caso de estudo principal foi considerado o modelo do conversor do processo de FCC desenvolvido por Moro e Odloak (1995). Mediante a metodologia de otimização do processo baseado no uso do modelo determinístico da planta, foram definidas estratégias e políticas operacionais para a operação da unidade de FCC em estudo. Procurou-se alto nível de desempenho e segurança operacional, através da integração das etapas de operação, otimização e controle no contexto de otimização em tempo real do processo. As otimizações foram divididas em quatro etapas: 1) Análises preliminares dos fatores e das variáveis de resposta do modelo do conversor foram realizadas usando a técnica de planejamento de experimentos, com o objetivo de compreender a interação entre elas, assim como obter modelos simplificados das variáveis de resposta. A geração dos modelos simplificados é devido à necessidade de ganho no tempo computacional permitindo o conhecimento prévio da região de otimização já que em casos industriais pode não ser possível representar adequadamente o processo por modelos determinísticos; 2) Otimização usando algoritmos genéticos implementados no modelo simplificado da conversão, e no modelo determinístico com e sem restrições; 3) Otimização considerando o método de otimização SQP implementado no modelo simplificado da conversão e no modelo determinístico com restrições; e 4) otimização multi-objetivo do conversor usando x a técnica dos algoritmos genéticos, com o objetivo de maximizar a conversão, assim como a minimização da vazão dos gases de combustão, especificamente o monóxido de carbono (CO). Das otimizações foram obtidos ganhos em torno de 8% na conversão quando comparado com os valores de conversão sem otimização. Finalmente, foi realizada a integração do modelo do processo, com a otimização e o controle, dando como resultado a otimização em tempo real do conversor de FCC. A variável de otimização foi a conversão e, através da implementação do controle por matriz dinâmica com restrições (QDMC), aplicando a metodologia de controle inferencial. As variáveis escolhidas como variável controlada foi a temperatura de reação e como variável manipulada foi a temperatura da alimentação, com perturbações na vazão de alimentação do ar de regeneração. Valores de conversão da ordem de 88% foram atingidos para o esquema de otimização em tempo real, o método de otimização por algoritmo genético apresentou um desempenho satisfatório, com tempos e cargas computacionais razoáveis para implementação desta metodologia, em nível industrial
Abstract: The purpose of this research was the develop of an optimization methodology. Experimental design technique along with a hybrid optimization methodology obtained by association of sequential quadratic programming (SQP) with genetic algorithms (GA), were implemented in the model of a Fluid Catalytic Cracking process (FCC) developed by Moro and Odloak (1995). This process is described for a heterogeneous, non isothermal system, in which a detailed modeling comprises mass and energy balance equations for catalyst particles, liquid and gaseous phases that makes this process model, a case study for implementing the optimization methodology developed. The process optimization methodology developed; along with the deterministic model of the plant were applied to define operational strategies and policies for the operation of the FCC unit studied aiming to obtain high performance and operational safety, through the integration of control, operation and optimization stages in the context of real-time optimization (RTO) process. Optimizations were divided into four stages: 1) Preliminary analysis of factors and response variables of converter modeling were performed using experimental design technique aiming to understand the factors and response variables interaction, as well as to obtain response variables simplified models to be used as objective function in optimization stages, 2) a optimization using genetic algorithms was implemented in the simplified conversion model, in the deterministic modeling and the deterministic model considering factors restrictions, 3) a optimization considering a local search methodology like sequential quadratic programming (SPQ) was implemented in the simplified model of process conversion and also it was consided the deterministic model with restrictions. As initial estimative, the optimum factor values obtained with genetic algorithms were considered as well as two random points in the search space, and 4) a multi objective optimization considering genetic algorithms technique in order to maximize conversion and minimize combustion gases emissions, specifically carbon monoxide was developed. Applying this optimization methodology was obtained increments of around 8% in the feed conversion when compared with conversion values without optimization. xii Finally, it was developed the integration of optimization, control and process modeling giving as result the real time optimization (RTO) of FCC converter. The variable maximized by genetic algorithms was the feed conversion and the control technique implemented was based on the matrix named (QDMC) in conjunction with inferential control methodology. It was considered as controlled variable the reaction temperature adjusting the feed temperature (manipulated variable), for disturbances in the feed flow of the regeneration air. Feed conversion in the order of 88% were achieved for the real time optimization scheme considered, in which, the genetic algorithm showed an excellent performance in reasonable computational times and computational loads for implementation at industrial level
Doutorado
Desenvolvimento de Processos Químicos
Doutor em Engenharia Química

This study utilizes a Monte Carlo simulation to examine the performance of multivariate geometric moving average control chart schemes for controlling the mean of a multivariate normal process. The study compares the performance of the proposed method with a multivariate Shewhart chart, a multiple univariate cumulative sum (CUSUM) control chart, a multivariate CUSUM control chart and a multiple univariate geometric moving average control chart.

Thesis (DTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009
The problem for effective and optimal control of wastewater treabnent plants is very important recently because of the increased requirements to the qualitY of the effluent The activated sludge process is a type of wastewater process characterized with complex dynamics and because of this proper control design and implementation strategies are necessary and important for its operation. Since the early seventies, when a major leap forward was made by the widespread introduction of dissolved oxygen control, little progress has been made. The most critical phase in the solution of any control problem is the modelling stage. The primary building block of any modem control exercise is to construct and identify a model for the system to be controlled. The existing full Activated Sludge Model 1 (ASM1) and especially University of Cape Town (UCT) models of the biological processes in the activated sludge process, called in the thesis biological models, are highly complex because they are characterised with a lot of variables that are difficult to be measured on-line, complex dependencies and nonlinear interconnections between the biological variables, many kinetic parameters that are difficult to be determined, . different time scales for the process dynamics. The project considers reduction of the impact of the complexity of the process model over the methods for control design and proposes a solution to the above difficulties by development of a reduced model with small number of variables, but still with the same characteristics as the original full model for the purposes of real time.

This thesis addresses the problem of defining the control law for human respiration. Seven different drivers have been identified as possibly having an input to the respiratory controller. These seven represent a combination of feedforward and feedback inputs arising from neural and humoral mechanisms. Using the assumption that carbon dioxide concentrations in the arterial blood have the strongest effect, a control equation with proportional and derivative components based on this driver was evaluated. The methodology for the evaluation was to create a model of the respiratory system incorporating the P/D controller, obtain experimental data of one test subject's respiratory response to exercise, then compare model generated output with experimental data, and adjust the parameters in the control equation to yield optimal model performance. The usual practice of testing controller performance has been to apply single step loads to a model and evaluate its response. A multi-step protocol was used here to provide a better, more generalized test of controller performance. This thesis may represent the first documented use of an approach of this type for evaluating respiratory controller performance. Application of a multi-step protocol revealed a non-linear controller was needed to keep pace with system changes. Respiratory system operation was effectively managed using a controller of the form: VENTILATION = F(dCO2/dT,Q) + F(CO2,Q) + CONSTANT.
Master of Science

Thesis (DTech (Chemistry))--Cape Peninsula University of Technology, 2005
A 2-factorial experiment, involving 3 levels of phosphorus (0, 40, and 80 kg P.ha-I ) as main treatment and 4 cropping systems (mono crop, maize/cowpea inter-row, maize/cowpea intra-row, and maize/cowpea intra-hole cropping) as sub-treatment was conducted in the field for 2 consecutive years in 2003 and 2004 to assess i) the effects of exogenous P supply and cropping system on the concentrations of plant-available nutrients in the rhizosphere of cowpea and maize; ii) the effect of exogenous P supply on tissue concentrations of minerals in nodulated cowpea and maize in mixed plant cultures iii) the effects of exogenous P supply and cropping system on plant growth and N2 fixation, and iv) the effects of exogenous P supply and cropping system on phosphatase activity and microbial biomass in the rhizosphere of cowpea and maize. At harvest, it was found that applying 40 or 80 kg P.ha-I significantly increased cowpea grain yields by 59-65% in 2003 and 44-55% in 2004. With maize, the increases in grain yield were 2037% in 2003 and 48-55% in 2004 relative to zero-P control. In both cropping seasons, the number of pod-bearing peduncles per plant, the number of pods per plant, the number of seeds per pod, and seed yield per cowpea plant were significantly increased with the application of exogenous P. In contrast, these parameters were all significantly depressed by mixed culture relative to mono crop cowpea. Intercropping maize with cowpea produced higher total yields per unit land area than the sole crop counterpart.

Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2005
Fennentation is the process that results in the fonnation ofalcohol or organic acids on the basis of growth of bacteria, moulds or fungi on different nutritional media (Ahmed et al., 1982). Fennentation process have three modes of operation i.e. batch, fed-batch and continuous ones. The process that interests a lot of control engineers is the fed-batch fennentation process (Johnson, 1989). The Fed-batch process for the production ofyeast is considered in the study. The fennentation is based on the Saccharomyces cerevisiae yeast. It grows in both aerobic and anaerobic environmental conditions with maximum product in the aerobic conditions, also at high concentration of glucose (Njodzi, 200I). Complexity of fed-batch fennentation process, non-linearity, time varying characteristics, application of conventional analogue controllers provides poor control due to problems in tuning individual loops and the process characteristics. The problem for control of the fed-batch process for the production of yeast is further complicated by the lack of on-line sensors, lack ofadequate models as a result ofpoorly understood dynamics. The lack of on-line sensors results in the impossibility oftuning the analogue controllers in real time. The process for propagation of yeast in aerobic conditions is considered in the dissertation. The experiments are conducted at the University of Cape Town (DCT), Department of Chemical Engineering with a bioreactor and bio-controller combined in a Biostat ® C lab scale plant (H. Braun Biotech International, 1996). The bio-controller has built in Pill controller loops for control variables, with the ability to adjust the controller parameters i.e. P, D and I through the serial interface (SeidIer, 1996).

In the operation of CMGs there exists a concept called “back drive,” which represents a case where the coupling effects of the angular velocity of the body and the angular momentum of the CMG overwhelm the input torque and result in a lack of control. This effect is known but not well documented or studied in the literature. Starting from first principles, this thesis derives the full nonlinear dynamical equations for CMGs. These equations contain significantly more terms than are found in the literature. As a means to understand the implications of these terms, a reduced order model is derived. The full and reduced models are then validated by means of extensive simulations. Finally, experimental verification of the models confirms the finding that the reduced order model provides a reasonably high fidelity for dynamics.

The analysis, finite element approximation, and numerical simulation of some control problems associated with fluid flows are considered. First, we consider a coupled solid/fluid temperature control problem. This optimization problem is motivated by the desire to remove temperature peaks, i.e., "hot spots", along the bounding surface of containers of fluid flows. The heat equation of the solid container is coupled to the energy equation for the fluid. Control is effected by adjustments to the temperature of the fluid at the inflow boundary. We give a precise statement of the mathematical model, prove the existence and uniqueness of optimal solutions, and derive an optimality system. We study a finite element approximation and provide rigorous error estimates for the error in the approximate solution of the optimality system. We then develop and implement an iterative algorithm to compute the approximate solution. Second, a computational study of the feedback control of the magnitude of the lift in flow around a cylinder is presented. The uncontrolled flow exhibits an unsymmetric Karman vortex street and a periodic lift coefficient. The size of the oscillations in the lift is reduced through an active feedback control system. The control used is the injection and suction of fluid through orifices on the cylinder; the amount of fluid injected or sucked is determined, through a simple feedback law, from pressure measurements at stations along the surface of the cylinder. The results of some computational experiments are given; these indicate that the simple feedback law used is effective in reducing the size of the oscillations in the lift. Finally, some boundary value problems which arise from a feedback control problem are considered. We give a precise statement of the mathematical problems and then prove the existence and uniqueness of solutions to the boundary value problems for the Laplace and Stokes equations by studying the boundary integral equation method.
Ph. D.

The time-varying survival rates of the carrot weevil, Listronotus oregonensis, were estimated by a new method. This method precluded the possibility of negative simulation survival rates. Analysis of carrot weevil population dynamics indicated that the egg mortality was density dependent with Anaphes sordidatus, an egg parasitoid, as a major density dependent factor. Larval mortality was less density dependent. Based on the mortality information, a simulation model for carrot weevil population dynamics was established. The simulation precision, evaluated by comparing simulated and observed egg and larval population dynamics, was satisfactory. Sensitivity analysis indicated that A. sordidatus had a large influence on carrot weevil population dynamics. The economic threshold for carrot weevil control in early carrots was 5 eggs/100 carrots at the peak population density. It ranged from 3.8 to 5.3 eggs/100 carrots in mid-season carrots depending on the selling price. A decision model showed that the best sowing date was after June 5 when risks were not considered. For risk aversion growers, sowing carrots between May 20 and May 31 was the best choice.

Thesis (MTech (Electrical Engineering))--Peninsula Technikon, Cape Town, 2002
Fermentation is the process that results in the formation of alcohol or organic acids on the basis of growth of bacteria, moulds or fungi on different nutritional media (Ahmed et al., 1982). Fermentation process have three modes of operation i.e. batch, fed-batch and continuous mode ofoperation. The process that interests a lot of control engineers is the fed-batch fe=entation process (Johnson, 1989). The Fed-batch process for the production ofyeast is considered in the study. The considered yeast in the study is the Saccharomyces cerevisiae. It grows in both aerobic and anaerobic environmental conditions with maximum product in the aerobic conditions, also at high concentration of glucose (Njodzi, 2001). Complexity of fedbatch fe=entation process, non-linearity, time varying characteristics, application of conventional analogue controllers provides poor control due to problems in tuning individual loops and the process characteristics. The problem for control of the fedbatch process for the production of yeast is further complicated by the lack of on-line sensors, lack of adequate models as a result of poorly understood dynamics. The lack of on-line sensors results in the impossibility of tuning the analogue controllers in real time. The process for propagation of yeast in aerobic conditions is considered in the dissertation. The experiments are conducted at the University of Cape Town (VCT), Department of Chemical Engineering with a bioreactor and bio-controller are combined in a Biostat ® C lab scale plant (B. Braun Biotech International, 1996). The bio-controller has built in PID controller loops for control variables, with the ability to adjust the controller parameters i.e. P, D and I through the serial interface (Seidler, 1996).

Approved for public release; distribution in unlimited.
This thesis considers the problem of time-optimal spacecraft slew maneuvers. Since the work of Bilimoria and Wie it has been known that the time-optimal reorientation of a symmetric rigid body was not the eigenaxis maneuver once thought to be correct. Here, this concept is extended to axisymmetric and asymmetric rigid body reorientations with idealized independent torque generating devices. The premise that the time-optimal maneuver is not, in general, an eigenaxis maneuver, is shown to hold for all spacecraft configurations. The methodology is then extended to include spacecraft control systems employing magnetic torque rods, a combination of pitch bias wheel with magnetic torque rods, and finally to control systems employing single gimbal control moment gyros. The resulting control solutions, designed within the limitations of the actuators, eliminate the requirement to avoid actuator singularities. Finally, by employing sampled-state feedback the viability of real-time optimal closed loop control is demonstrated.

This paper presents a Lagrangian formulation for studying the dynamics and control of the proposed Space Station based Mobile Servicing System (MSS) for a particular case of in plane libration and maneuvers. The simplified case is purposely considered to help focus on the effects of structural and joint flexibility parameters of the MSS on the complex interactions between the station and manipulator dynamics during slewing and translational maneuvers. The response results suggest that under critical combinations of parameters, the system can become unstable. During maneuvers, the deflection of the MSS can become excessive, leading to positioning error of the payload. At the same time the libration error can also be significant. A linear quadratic regulator is designed to control the deflection of the manipulator and maintain the station at its operating configuration.
Applied Science, Faculty of
Mechanical Engineering, Department of
Graduate

Doctor of Philosophy
Department of Industrial & Manufacturing Systems Engineering
David H. Ben-Arieh
Chih-Hang Wu
Patients who suffer from sepsis or septic shock are of great concern in the healthcare system. Recent data indicate that more than 900,000 severe sepsis or septic shock cases developed in the United States with mortality rates between 20% and 80%. In the United States alone, almost $17 billion is spent each year for the treatment of patients with sepsis. Clinical trials of treatments for sepsis have been extensively studied in the last 30 years, but there is no general agreement of the effectiveness of the proposed treatments for sepsis. Therefore, it is necessary to find accurate and effective tools that can help physicians predict the progression of disease in a patient-specific way, and then provide physicians recommendation on the treatment of sepsis to lower risk for patients dying from sepsis. The goal of this research is to develop a risk assessment tool and a risk management tool for sepsis. In order to achieve this goal, two system dynamic mathematical models (SDMMs) are initially developed to predict dynamic patterns of sepsis progression in innate immunity and adaptive immunity. The two SDMMs are able to identify key indicators and key processes of inflammatory responses to an infection, and a sepsis progression. Second, an integrated-mathematical-multi-agent-based model (IMMABM) is developed to capture the stochastic nature embedded in the development of inflammatory responses to a sepsis. Unlike existing agent-based models, this agent-based model is enhanced by incorporating developed SDMMs and extensive experimental data. With the risk assessment tools, a Markov decision process (MDP) is proposed, as a risk management tool, to apply to clinical decision-makings on sepsis. With extensive computational studies, the major contributions of this research are to firstly develop risk assessment tools to identify the risk of sepsis development during the immune system responding to an infection, and secondly propose a decision-making framework to manage the risk of infected individuals dying from sepsis. The methodology and modeling framework used in this dissertation can be expanded to other disease situations and treatment applications, and have a broad impact to the research area related to computational modeling, biology, medical decision-making, and industrial engineering.

Position and vibration control of a flexible beam is studied analytically and in the laboratory. Two different motor types are compared as actuators throughout the thesis: a standard voltage controlled motor and a torque controlled motor. The experimental beam is controlled with a dc-servo motor at its base and is instrumented with strain gages and a potentiometer. The control law is a form of linear, direct-output feedback. State estimators augment the control law to provide rate information that is not available from the instrumentation. Accurate modeling of the system’s inherent damping characteristics is achieved by analyzing experimental data. Gains were iterated yielding minimum-gain norm and minimum-sensitivity norm solutions to meet imposed eigenvalue placement constraints. Results for the two solutions and the two systems are compared and contrasted. Experimental verification of analytical results is hampered by unmodeled system non-linearities. Several attempts at bypassing these obstacles are shown. Finally, conclusions and recommendations are made.
Master of Science
incomplete_metadata

Interacting species systems have complex dynamics that are often subject to change due to internal and external factors. Quantitative modelling approaches to capture demographic fluctuations can be insufficient in the presence of stochastic variation and uncertainty. This thesis establishes new modelling techniques to account for such demographic variations and develops novel numerical simulation tools for solving these systems. These explorations are extended for solving invasive species management problems where robust management actions and efficient use of allocated budgets are necessary.

This dissertation is concerned with some topics in the modeling and control of large flexible structures. In the finite element convergence toward the natural modes and frequencies of a structure, it is found that two mechanisms limiting the accuracy of higher modes are, first, a decrease in the number of active degrees of freedom for higher mode approximations due to orthogonality constraints, and, second, the fact that lower computed, rather than actual, eigenfunctions appear in the orthogonality constraints, so that inaccuracy in lower modes inhibits convergence to higher modes. Refining the elements using the hierarchical p-version proves to be far superior to refining the mesh, as demonstrated by numerical examples. In the third chapter, a method is presented for solving the algebraic eigenvalue problem for a structure, which combines attractive features of the subspace iteration method and the component-mode synthesis methods. Reduced substructure models are generated automatically and coupled exactly to form a reduced structure model, whose eigensolution is used to refine the substructure models. Convergence is much faster than in the subspace iteration method, as demonstrated by numerical examples. In the fourth chapter, the effectiveness of modal control (IMSC) and direct feedback control, in which the actuator force depends only on the local velocity and displacement, are investigated for suppressing traveling waves on a string and on a beam, both with slight material damping. Direct feedback proves superior for the string, as more modes must be controlled than can be handled by modal control with a limited number of actuators, but inferior for the beam, as effort is wasted suppressing motion in higher modes where damping is pervasive, while modal control focuses effort on those lower modes which need to be controlled. The optimal vibration control for a distributed system subjected to persistent excitation is not available, so a two-part control is proposed in chapter five for suppressing the motion of a distributed system with a moving support. The first part cancels the moving support's excitation to an optimal extent, and the second is a direct velocity feedback control. A numerical example demonstrates the effectiveness of this control method.
Ph. D.
incomplete_metadata

This work presents an investigation into the parameter estimation of suspension components and the vertical motions of wheeled vehicles from experimental data. The estimation problems considered were for suspension dampers, a single wheel station and a full vehicle. Using conventional methods (gradient-based (GB), Downhill Simplex (DS)) and stochastic methods (Genetic Algorithm (GA) and Differential Evolution (DE)), three major problems were encountered. These were concerned with the ability and consistency of finding the global optimum solution, time consumption in the estimation process, and the difficulties in setting the algorithm's control parameters. To overcome these problems, a new technique named the discrete variable Hybrid Differential Evolution (dvHDE) method is presented. The new dvHDE method employs an integer-encoding technique and treats all parameters involved in the same unified way as discrete variables, and embeds two mechanisms that can be used to deal with convergence difficulties and reduce the time consumed in the optimisation process. The dvHDE algorithm has been validated against the conventional GB, DS and DE techniques and was shown to be more efficient and effective in all but the simplest cases. Its robustness was demonstrated by its application to a number of vehicle related problems of increasing complexity. These include case studies involving parameter estimation using experimental data from tests on automotive dampers, a single wheel station and a full vehicle. The investigation has shown that the proposed dvHDE method, when compared to the other methods, was the best for finding the global optimum solutions in a short time. It is recommended for nonlinear vehicle suspension models and other similar systems.

This work presents an investigation into the parameter estimation of suspension components and the vertical motions of wheeled vehicles from experimental data. The estimation problems considered were for suspension dampers, a single wheel station and a full vehicle. Using conventional methods (gradient-based (GB), Downhill Simplex (DS)) and stochastic methods (Genetic Algorithm (GA) and Differential Evolution (DE)), three major problems were encountered. These were concerned with the ability and consistency of finding the global optimum solution, time consumption in the estimation process, and the difficulties in setting the algorithm's control parameters. To overcome these problems, a new technique named the discrete variable Hybrid Differential Evolution (dvHDE) method is presented. The new dvHDE method employs an integer-encoding technique and treats all parameters involved in the same unified way as discrete variables, and embeds two mechanisms that can be used to deal with convergence difficulties and reduce the time consumed in the optimisation process. The dvHDE algorithm has been validated against the conventional GB, DS and DE techniques and was shown to be more efficient and effective in all but the simplest cases. Its robustness was demonstrated by its application to a number of vehicle related problems of increasing complexity. These include case studies involving parameter estimation using experimental data from tests on automotive dampers, a single wheel station and a full vehicle. The investigation has shown that the proposed dvHDE method, when compared to the other methods, was the best for finding the global optimum solutions in a short time. It is recommended for nonlinear vehicle suspension models and other similar systems.

Thesis (Ph.D)--Chemical Engineering, Georgia Institute of Technology, 2008.
Committee Chair: Gallivan, Martha A.; Committee Member: Hess, Dennis; Committee Member: Lee, Jay H.; Committee Member: Li, Mo; Committee Member: Ludovice, Pete.

Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009
This project was started as a result of strict environmental and health regulations together with a demand tor cost effective operation of wastewater treatment plants (VVWTPs). The main aim of this project is how to keep effluent concentration below a prescribed limit at the lowest possible cost. Due to large fluctuations in the quality and quantity of the influent concentrations, traditional control methods are not adequate to achieve this aim The major drawback with these methods is that the disturbances affect the process before the controller has time to correct the error (Olsson and Newell, 1999: 454). This problem is addressed through the use of modern control systems. Modern control systems are model based predictive algorithms arranged as feed-forward controllers (Olsson and Newell. 1999: 454). Normally a controller is equipped with a constant set point; the goal In this project is to calculate an optimal DO trajectory that may be sampled to provide a varying optimal set-point for the Activated Sludge Process, In this project an optimal control problem Is formulated using DO concentration as a control variable. This requires a model of the process to be controlled a mathematical expressions of the limitations on the process input and output variables and finally the objective functional. which consists of the objectives of the control. The structures of the Benchmark plant (developed within the COST 682 working group) and the Athlone WWTPs are used to implement this opt.mat control strategy in MATLAB. The plant's full models are developed based on the mass balance principle incorporating the activated sludge biological models: ,ASM1, ASM2, ASM2d and ASM3 (developed by the IWA working groups). To be able to develop a method that may later on be used for online control, the full models are reduced based on the technique In Lukasse (1996). To ensure that the reduced models keep the same prediction capabilities as the full models, parameters of the reduced models are calculated based on the Least Squares principle, The formulated optimal control problem is solved based on the decompostion-coorcdination method that involves time decomposition in a two layer structure. MATLAB software [5 developed to solve the problems for parameter estimation. fun and reduced mode! simulation. and optimal control calculation for the considered different cases of plant structures and biological models. The obtained optimal 00 trajectories produced the effluent state trajectories within prescribed requirements. These DO trajectories may be implemented in different SCADA systems to be tracked as set points or desired trajectories by different types of controllers.

Orientador: Reinaldo Charnet
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica
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Resumo: Neste trabalho é apresentado uma alternativa de controle estatístico de processo, quando o mesmo apresenta interdependência nos seus dados, sendo a ferramenta carta de controle o instrumento mais adequado para realizar a tarefa de distinção dos dois tipos de causas de variação existentes em todo tipo de processo. Os modelos de previsão baseados nas séries temporais assumem grande importância quando se deseja controlar processos que produzem séries de dados autocorrelacionados. Esses modelos consideram exatamente a situação de termos observações autocorrelacionadas, daí a sua importância como modelo de previsão para séries temporais. Para ilustrar esse trabalho, foi apresentado um estudo de caso de uma indústria química, cujo processo é aucorrelacionado, ou seja, os dados iniciais do processo prolongam sua influencia durante algum tempo nos dados subseqüentes. A variável de interesse é a contaminação de ferro no produto final, que desde o início do processo é medida, tentando-se controlar essa contaminação num patamar que não prejudique a utilização do produto pelo cliente. Com o modelo ajustado a proposta foi controlar os resíduos desse modelo, ou seja, o que o modelo não ajustou (resíduos = previsto - real) deveria ficar compreendido entre limites de controle com uma média igual a zero
Abstract: This work presents an alternative model for statistical control of the process when we have auto correlated data. The traditional methods suggest the control chart as the most appropriate tool to be used for the identification of the two different sources of variation for alI types of processes. The prediction models based on time series play an important role when the main purpose is in controlling those processes that produce series of auto correlated dada. Box Jenkins models deal specificalIy with those situations of auto correlated data and this brings up its importance as a prediction model in time series analysis. A case study conducted in a chemical industry is presented as an example of one application of the suggested model, once it deals with an auto correlated process in which the initial data extend its influence on subsequent data for a certain period o time. The main variable of interest in this case study is the contamination of iron in the final product. This variable has been evaluated since the beginning of the process attempting to control the contamination of iron in the product in a level such that its utilization does not cause any damage to the customer. With this adjusted model the purpose is to control the residuals (predicted - observed) which should remain inside the interval determined by the control limits with mean zero
Mestrado
Gestão da Qualidade Total
Mestre em Engenharia Mecânica

This thesis is focused on airport departure operations; its objective is to assign a value to surface surveillance information within a collaborative framework. The research develops a cooperative concept that improves the control of departure operations at busy airports and evaluates its merit using a classical and widely accepted airport departure model. The research then assumes departure operations are collaboratively controlled and develops a stochastic model of taxi operations on the airport surface. Finally, this study investigates the effect of feeding back different levels of surface surveillance information to the departure control process. More specifically, it examines the environmental and operational impact of aircraft surface location information on the taxi clearance process. Benefits are evaluated by measuring and comparing engine emissions for given runway utilization rates.

This thesis describes an investigation on the blowout phenomenon in gas turbine combustors. The combustor primarily used for this study was a swirl- and dump-stabilized, atmospheric pressure device, which did not exhibit dynamic combustion instabilities. The first part of the thesis work concentrated on finding a sensing methodology to be able to predict the onset of approach of combustor blowout using optical methods. Temporary extinction-reignition events that occurred prior to blowout were found to be precursor events to blowout. A threshold based method was developed to identify these events in the time-resolved sensor output. The number and the average length of each event were found to increase as the LBO limit (fuel-air ratio) is approached. This behavior is used to predict the proximity to lean blowout. In the second part of this study, the blowout sensor was incorporated into a control system that monitored the approach of blowout and then actuated an alternate mechanism to stabilize the combustor near blowout. Enhanced stabilization was achieved by redirecting a part of the main fuel to a central preinjection pilot injection. The sensing methodology, without modification, was effective for the combustor with pilot stabilization. An event based control algorithm for controlling the combustor from blowing out was also developed in this study. The control system was proven to stabilize the combustor even when the combustor loading was rapidly changed. The final part of this study focused on understanding the physical mechanisms behind the precursor events. High speed movies of flame chemiluminescence and laser sheet scattering from oil droplets seeded into the reactants were analyzed to explain the physical processes that cause the extinction and the reignition of the combustor during a precursor event. A physical model for coupling of the fluid dynamics of vortex breakdown and combustion during precursor and blowout events is proposed. This model of blowout phenomenon, along with the sensing and control strategies developed in this study could enable the gas turbine combustor designers to design combustors with wider operability regimes. This could have significant payoffs in terms of reduction in NOx emissions from the combustor.

Thesis (MSc)--Stellenbosch University, 2015
AFRIKAANSE OPSOMMING : Die groeiende belangstelling in kalibrering en modelrisiko is ’n redelik resente ontwikkeling in finansiële wiskunde. Hierdie proefskrif fokusseer op hierdie sake, veral in verband met die prysbepaling van vanielje-en eksotiese opsies, en vergelyk die prestasie van verskeie Lévy modelle. ’n Nuwe metode om modelrisiko te meet word ook voorgestel (hoofstuk 6). Ons kalibreer eers verskeie Lévy modelle aan die log-opbrengs van die S&P500 indeks. Statistiese toetse en grafieke voorstellings toon albei aan dat suiwer sprongmodelle (VG, NIG en CGMY) die verdeling van die opbrengs beter beskryf as die Black-Scholes model. Daarna kalibreer ons hierdie vier modelle aan S&P500 indeks opsie data en ook aan "CGMY-wˆ ereld" data (’n gesimuleerde wÃłreld wat beskryf word deur die CGMY-model) met behulp van die wortel van gemiddelde kwadraat fout. Die CGMY model vaar beter as die VG, NIG en Black-Scholes modelle. Ons waarneem ook ’n effense verskil tussen die nuwe parameters van CGMY model en sy wisselende parameters, ten spyte van die feit dat CGMY model gekalibreer is aan die "CGMYwêreld" data. Versperrings-en terugblik opsies word daarna geprys, deur gebruik te maak van die gekalibreerde parameters vir ons modelle. Hierdie pryse word dan vergelyk met die "ware" pryse (bereken met die ware parameters van die "CGMY-wêreld), en ’n beduidende verskil tussen die modelpryse en die "ware" pryse word waargeneem. Ons eindig met ’n poging om hierdie modelrisiko te kwantiseer
ENGLISH ABSTRACT : The growing interest in calibration and model risk is a fairly recent development in financial mathematics. This thesis focussing on these issues, particularly in relation to the pricing of vanilla and exotic options, and compare the performance of various Lévy models. A new method to measure model risk is also proposed (Chapter 6). We calibrate only several Lévy models to the log-return of S&P500 index data. Statistical tests and graphs representations both show that pure jump models (VG, NIG and CGMY) the distribution of the proceeds better described as the Black-Scholes model. Then we calibrate these four models to the S&P500 index option data and also to "CGMY-world" data (a simulated world described by the CGMY model) using the root mean square error. Which CGMY model outperform VG, NIG and Black-Scholes models. We observe also a slight difference between the new parameters of CGMY model and its varying parameters, despite the fact that CGMY model is calibrated to the "CGMY-world" data. Barriers and lookback options are then priced, making use of the calibrated parameters for our models. These prices are then compared with the "real" prices (calculated with the true parameters of the "CGMY world), and a significant difference between the model prices and the "real" rates are observed. We end with an attempt to quantization this model risk.

Orientador: João Bosco Ribeiro do Val
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: O problema de rastreamento de alvos é tratado de diversas formas na literatura, seja elaborando modelos matemáticos mais eficientes na reprodução da dinâmica de movimentos, seja na construção de filtros estocásticos que realizem estimativa de estados, como de posição e velocidade. Quando se trata do rastreamento em que os alvos de interesse são diversos indivíduos em movimento, a literatura não possui estudos específicos. Dessa forma, o objetivo principal da tese é aprofundar o conhecimento de rastreamento de indivíduos. Neste cenário, existe um número elevado e variável de alvos, que podem surgir de forma espontânea, agrupar-se ou separar-se, além de alarmes falsos imersos nas medidas. Estudou-se a teoria dos Conjuntos Aleatórios Finitos, cujo tratamento matemático se dá através do chamado Cálculo Multi-Alvo. Os filtros estocásticos também foram estudados sobre este ponto de vista, sendo os filtros PHD e GM-PHD os principais. Criada essa base teórica, três propostas baseadas nesse problema foram apresentadas: Modelos de Movimentação de Indivíduos, Simulador de Trajetórias de Indivíduos e Modelos Dinâmicos para Filtragem Estocástica. A primeira das propostas consiste em construir perfis probabilísticos de movimentação para cada um dos indivíduos. A segunda envolve a criação de um simulador de trajetórias de indivíduos que seja o mais verossímil possível em relação às trajetórias reais de uma pessoa, em cenários com variações de terreno, classificados pela dificuldade de locomoção. E finalmente, a terceira proposta tem como objetivo criar um modelo dinâmico combinado e modificado em relação a modelos encontrados na literatura para ser inserido no processo de filtragem estocástica. Ao final, alguns testes e simulações foram realizados, de tal forma a testar o desempenho de filtros e analisar o comportamento dos modelos matemáticos e dos perfis probabilísticos propostos
Abstract: The problem of target tracking is handled in different ways in the literature, either developing more efficient mathematical models to reproduce the dynamics of movements, or building stochastic filters that perform state estimation, such as position and velocity. When it comes to target tracking where the targets of interest are many individuals in motion, the literature lacks on specific studies. Thus, the main objective of the thesis is to deepen the knowledge of individuals tracking. In this scenario, there is a large and variable number of targets, which may arise spontaneously, group together or separate, in addition to measures immersed in false alarms. A study of the Random Finite Sets theory was made, whose mathematical treatment is through the so-called Multi-Target Calculus. Stochastic filters were also studied on this point of view, where the PHD and the GM-PHD filters are the main ones. After created the theoretical basis, three proposals based on this problem were presented: Motion Models for Individuals, a Simulator for Individuals Trajectories and Dynamic Models for Stochastic Filtering. The first proposal is based on building a motion probabilistic shape for each individual. The second proposal involves the creation of a trajectory simulator for individuals to be as plausible as possible to the real movements of a person, in scenarios with variations of terrain, ranked by locomotion difficulty. And finally, the third proposal aims to create a combined and modified dynamic model from models found in the literature, to be inserted in the stochastic filters. Finally, several tests and simulations were made in such a way to test the filters performances and analyze the behavior of the proposed mathematical models and the motion probabilistic shapes
Doutorado
Automação
Doutor em Engenharia Elétrica

Neste trabalho são discutidos e avaliados métodos de construção de conjuntos de sinais de excitação para identificação de sistemas. Esse estudo é realizado tendo como objetivo aplicações na indústria de processos, particularmente no refino de petróleo. As restrições operacionais da indústria de refino de petróleo estão cada vez mais severas em virtude do aumento da demanda energética, qualidade de derivados, variações de preço de petróleo, concorrência no mercado de derivados e outros fatores econômicos, ambientais e de eficiência energética. Nesse cenário, é crescente o uso de técnicas de controle preditivo por modelos e, consequentemente, a demanda por identificação de plantas de processamento. As características particulares das plantas de processamento e de sua operação impõem restrições ao projeto e à aplicação de sinais de excitação. Vários métodos de construção de sinais encontrados na literatura e outros três propostos neste trabalho são avaliados e comparados com referência ao atendimento a essas restrições. Uma das principais restrições para a aplicação de sinais de excitação para identificação é relativa ao tempo disponível para excitação da planta. Assim, para o bom uso desse período, faz-se necessário garantir o sucesso de um experimento previamente à sua realização. Na literatura, encontram-se várias medidas de desempenho de sinais de excitação possíveis de serem obtidas previamente ao experimento de identificação. Neste trabalho, s~ao propostas duas novas medidas que complementam essas na avaliação dos conjuntos de sinais previamente ao experimento. A eficácia dos métodos de construção e das medidas de desempenho de sinais de excitação é avaliada por meio de simulação de identificação multivariável de duas plantas típicas de refinarias. As conclusões deste trabalho apresentam em síntese essas avaliações, como também sugestões de trabalhos futuros que visam à continuidade da pesquisa desenvolvida aqui.
In this work methods for generating sets of excitation signals for system identification are discussed and evaluated. This study is focused on applications in the process industries, particularly in oil refining. The operational constraints of the oil refining industry are becoming increasingly severe due to increased energy demand, quality of products, oil price variations,market competition and other economic, environmental and energy efficiency factors. In this scenario the use of model predictive control techniques is increasing, thus the demand for plant identification as well. The particular characteristics of the processing plants impose restrictions to the project and application of excitation signals. Various methods for generating signals accessible in the literature and three new others proposed in this work are compared with reference to these restrictions. One of the main constraints for applying excitation signals for identification is relative to the period available for excitation of the plant. Thus, for the proper use of this time interval, it is necessary to ensure the success of an experiment prior to its implementation. In the literature there are several performance measurements for evaluation of sets of excitation signals prior to the experiment. This work proposes two new measures to complement the evaluation. The effectiveness of the generating methods and performance measurements for excitation signals is evaluated by simulation of multivariable identification of two typical oil refining plants. The conclusions of this work briefly present these evaluations, as well as some suggestions of future work for the continuity of the current research.

Este trabalho propõe desenvolver um projeto de controle de um sistema de geração de vapor composto por múltiplas caldeiras que contemple a otimização do consumo de combustível do sistema. Para atingir este objetivo, deve-se combinar um controle regulatório eficiente de uma caldeira e um mecanismo divisor de carga eficiente para que cada caldeira opere com a confiabilidade normalmente requerida, aliado a um ponto ótimo de consumo de combustível. Esta dissertação apresenta: a modelagem dinâmica de uma caldeira aquatubular industrial; a implementação computacional do modelo dinâmico de uma caldeira aquatubular em Matlab; o projeto de controle de uma caldeira aquatubular no sistema de automação 800xA envolvendo a definição de estratégias de controle, a comunicação do sistema de automação com o modelo da planta no Matlab, uma avaliação sobre algumas técnicas de sintonia, bem como a sua simulação dinâmica e resultados; o problema de otimização para minimização do consumo de total de combustível de um sistema de geração de vapor com múltiplas caldeiras, bem como a avaliação de sua resolução com modelagem por uma abordagem de Programação Linear Inteira Mista; e o projeto de controle de um sistema com múltiplas caldeiras, envolvendo também a simulação dinâmica. Com base nos experimentos simulados considerou-se que a estratégia de controle proposta neste trabalho tem desempenho satisfatório, principalmente pelo fato de que a inclusão do bloco divisor de carga não acarretou prejuízo na característica de rejeição de perturbações, o que encoraja estudos posteriores com o objetivo de se ter uma utilização prática.
This study proposes to develop a control project for a multiple boilers steam generation system that includes fuel optimization. To achieve that, it must combine an efficient boiler regulatory control and an efficient mechanism for load allocation to each boiler in order to operate with normally required reliability and combined with optimum fuel consumption. This dissertation presents: dynamic modeling of an industrial watertube boiler; computational implementation of the dynamic watertube Boiler model in Matlab, the control design of a watertube Boiler in 800xA automation system involving the definition of control strategies, communication of the 800xA automation system with the plant model in Matlab, an evaluation of some techniques for PID tuning including dynamic simulation results, the optimization problem to minimize the total fuel consumption of a multiple boilers steam generation system, as well as the assessment of their resolution with Mixed Integer Linear Programming modeling approach, and control design of a multiple boilers system, also involving dynamic simulation. Based on simulated experiments it was found that the control strategy proposed in this work has satisfactory performance, mainly because of the inclusion of the divider block load did not affect the rejection of disturbances characteristic, which encourages further studies with objective of practical use.

This thesis presents several problems based on papers written jointly by the author and Dr. Christian-Oliver Ewald. Firstly, the author extends the model presented by Fershtman and Nitzan (1991), which studies a deterministic differential public good game. Two types of volatility are considered. In the first case the volatility of the diffusion term is dependent on the current level of public good, while in the second case the volatility is dependent on the current rate of public good provision by the agents. The result in the latter case is qualitatively different from the first one. These results are discussed in detail, along with numerical examples. Secondly, two existing lines of research in game theoretic studies of fisheries are combined and extended. The first line of research is the inclusion of the aspect of predation and the consideration of multi-species fisheries within classical game theoretic fishery models. The second line of research includes continuous time and uncertainty. This thesis considers a two species fishery game and compares the results of this with several cases. Thirdly, a model of a fishery is developed in which the dynamic of the unharvested fish population is given by the stochastic logistic growth equation and it is assumed that the fishery harvests the fish population following a constant effort strategy. Explicit formulas for optimal fishing effort are derived in problems considered and the effects of uncertainty, risk aversion and mean reversion speed on fishing efforts are investigated. Fourthly, a Dixit and Pindyck type irreversible investment problem in continuous time is solved, using the assumption that the project value follows a Cox-Ingersoll- Ross process. This solution differs from the two classical cases of geometric Brownian motion and geometric mean reversion and these differences are examined. The aim is to find the optimal stopping time, which can be applied to the problem of extracting resources.

Thesis (Ph. D.)(Metallurgical Engineering)--University of Pretoria, 2004.
Title from opening screen (viewed March 14, 2005). Summaries in English and Afrikaans. Includes bibliographical references.

Tesis por compendio
[ES] Algunos productos se caracterizan por su falta de homogeneidad, lo que significa que productos con diferentes características pueden ser obtenidos de un mismo proceso de producción debido a factores incontrolables como la naturaleza de las materias primas o las condiciones ambientales durante la producción. Hay cuatro aspectos que caracterizan la falta de homogeneidad en el producto: los subtipos homogéneos que se obtienen de un mismo lote de producción, la cantidad de productos que componen cada subtipo, el valor de cada uno de los subtipos, y el estado de los productos. La falta de homogeneidad en el producto dificulta la gestión de los procesos de las empresas y cadenas de suministro en el momento en el que los clientes requieren homogeneidad entre las unidades de producto que adquieren. Un ejemplo de esto se produce en el sector de la cerámica, en el que los clientes requieren que todas las unidades que van a ser ensambladas juntas tengan el mismo color, espesor y calidad por razones estéticas y de seguridad. Otro ejemplo es el extraído del sector agroalimentario, en el que el mercado final requiere productos que cumplan con un tamaño mínimo, un color particular, o sabor en el caso de las frutas. Además, el sector agroalimentario tiene la complejidad añadida producida por el deterioro de los productos a lo largo del tiempo, y la necesidad de los mercados de ofrecer a los clientes productos con una mínima duración tras su venta. En esta Tesis, se define como productos heterogéneos a aquellos productos que se pueden clasificar en subtipos homogéneos con una cantidad variable, mientras que los productos perecederos son aquellos que, además de ser heterogéneos, tienen falta de homogeneidad en su estado. De acuerdo con estos conceptos, el sector cerámico comercializa productos heterogéneos mientras que el sector agroalimentario comercializa productos perecederos. Esta Tesis propone marcos conceptuales y modelos de Investigación Operativa que soporten la gestión de cadenas de suministro con productos heterogéneos y perecederos en la toma de decisiones centralizada y distribuidas relacionadas con los niveles de decisión estratégica, táctica y operativa. El objetivo es mejorar la competitividad, sostenibilidad y flexibilidad de la cadena de suministro para adaptarse a los requerimientos del mercado bajo condiciones de incertidumbre. Para esto, se han propuesto modelos de Investigación Operativa deterministas e inciertos, cuyos resultados se comparan concluyendo que los resultados obtenidos con los modelos inciertos se adaptan mejor al comportamiento real de las cadenas de suministros.Los modelos de Investigación Operativa propuestos han contribuido a tres áreas de investigación: problemas operativos en el sector cerámico, problemas estratégicos en el sector agroalimentario y problemas de planificación en el sector agroalimentario. Las principales novedades en los problemas operativos en el sector cerámico son el modelado de las características de las baldosas cerámicas, la consideración de los requerimientos de homogeneidad entre unidades de diferentes líneas de pedido, y la posibilidad de realizar entregas parciales y entregas con retraso. Esta Tesis contribuye a los problemas estratégicos en el sector agroalimentario al diseñar una cadena de suministro completa de productos agroalimentarios frescos considerando el aspecto perecedero de los productos e integrando decisiones tácticas, y determinando el impacto real que tiene considerar el aspecto perecedero de los productos durante el diseño de la cadena de suministro ...
[CA] Alguns productes es caracteritzen per la seua falta d'homogeneïtat, el que significa que productes amb diferents característiques poden ser obtinguts d'un mateix procés de producció degut a factors incontrolables com la naturalesa de les matèries primeres o les condicions ambientals durant la producció. Hi ha quatre aspectes que caracteritzen la falta d'homogeneïtat en el producte: els subtipus homogenis que s'obtenen d'un mateix lot de producció, la quantitat de productes que componen cada subtipus, el valor de cada un dels subtipus, i l'estat dels productes. La falta d'homogeneïtat en el producte dificulta la gestió dels processos de les empreses i cadenes de subministrament en el moment en què els clients requerixen homogeneïtat entre les unitats de producte que adquirixen. Un exemple d'açò es produïx en el sector de la ceràmica, en el que els clients requerixen que totes les unitats que seran acoblades juntes tinguen el mateix color, grossària i qualitat per raons estètiques i de seguretat. Un altre exemple és l'extret del sector agroalimentari, en el que el mercat final requerix productes que complisquen amb una grandària mínima, un color particular, o sabor en el cas de les fruites. A més, el sector agroalimentari té la complexitat afegida produïda pel deteriorament dels productes al llarg del temps, i la necessitat dels mercats d'oferir als clients productes amb una mínima duració després de la seua venda. En aquesta Tesi, es definix com a productes heterogenis a aquells productes que es poden classificar en subtipus homogenis amb una quantitat variable, mentres que els productes peribles són aquells que, a més de ser heterogenis, tenen falta d'homogeneïtat en el seu estat. D'acord amb aquests conceptes, el sector ceràmic comercialitza productes heterogenis mentres que el sector agroalimentari comercialitza productes peribles. Aquesta Tesi proposa marcs conceptuals i models d'Investigació Operativa que suporten la gestió de cadenes de subministrament amb productes heterogenis i peribles en la presa de decisions centralitzada i distribuïdes relacionades amb els nivells de decisió estratègica, tàctica i operativa. L'objectiu és millorar la competitivitat, sostenibilitat i flexibilitat de la cadena de subministrament per adaptar-se als requeriments del mercat sota condicions d'incertesa. Per a açò, s'han proposat models d'Investigació Operativa deterministes i incerts, els resultats es comparen concloent que els resultats obtinguts amb els models incerts s'adapten millor al comportament real de les cadenes de subministraments. Els models d'Investigació Operativa proposats han contribuït a tres àrees d'investigació: problemes operatius en el sector ceràmic, problemes estratègics en el sector agroalimentari i problemes de planificació en el sector agroalimentari. Les principals novetats en els problemes operatius en el sector ceràmic són el modelatge de les característiques de les rajoles ceràmiques, la consideració dels requeriments d'homogeneïtat entre unitats de diferents línies de comanda, i la possibilitat de realitzar lliuraments parcials i lliuraments amb retard. Aquesta Tesi contribueix als problemes estratègics en el sector agroalimentari al dissenyar una cadena de subministrament completa de productes agroalimentaris frescos considerant l'aspecte perible dels productes, integrant decisions tàctiques, i determinant l'impacte real que té considerar l'aspecte perible dels productes durant el disseny de la cadena de subministrament ...
[EN] Some products are characterised by their lack of homogeneity, what means that products with different characteristics can be obtained from the same production process due to uncontrollable factors such as the nature of raw materials or the environmental conditions during production. There are four aspects that characterize the lack of homogeneity in the product: the homogeneous subtypes to be obtained from a production lot, the quantity of products that belong to each subtype, the value related to each of the subtypes and the state of the products. The lack of homogeneity in the product hinders the management of the supply chain or company's processes at the time customers require the homogeneity among the acquired units of product. An example of this is produced in the ceramic tile sector, in which customers need all acquired ceramic tiles that are going to be jointly assembled to have the same colour, thickness and quality for aesthetic and safety reasons. Another example is the extracted from the agri-food sector, in which final markets require products that meet some characteristics such as a minimum size, a particular colour or flavour in the case of fruits. In addition, the agri-food sector has the added complexity produced by the deterioration of products over time, and the need of markets to offer to end consumers products with a minimum durability after sale. In this Thesis, heterogeneous products are defined as products for which different subtypes can be obtained in a variable quantity while perishable products are those that, apart from being heterogeneous, have a lack of homogeneity in their state. According to these concepts, ceramic sectors would commercialize heterogeneous products while the agri-food sector would do so with perishable products. This Thesis proposes conceptual frameworks and Operations Research models to support the management of supply chains with heterogeneous and perishable products in centralized and distributed decision-making processes related to strategic, tactical and operative decisional levels. The objective is to improve the supply chain competitiveness, sustainability and flexibility to adapt to market requirements under uncertain conditions. For this, both deterministic and uncertain Operations Research models have been proposed, whose results are compared concluding that results obtained with uncertain models better fit with the behaviour of real supply chains. The proposed Operations Research models have contributed to three research areas: operational problems in the ceramic sector, strategic problems in the agri-food sector and planning problems in the agri-food sector. Main novelties in the ceramic operational problems are the modelling of the characteristics of ceramic tile products, the consideration of homogeneity requirements between units from different order lines, and the possibility of making partial deliveries and delayed deliveries. This Thesis contributes to strategic problems in agri-food products by designing an entire fresh agri-food supply chain considering the perishability of products and integrating tactical decisions, and by determining the real impact that considering the products' perishability has on the supply chain design process ...
This Thesis has been developed in the Research Centre of Management and Production Engineering (CIGIP, for its acronym in Spanish “Centro de Investigación en Gestión e Ingeniería de Producción”) of the Universitat Politècnica de València with the support of the predoctoral grant Programme of Formation of University Professors (FPU, for its acronym in Spanish “Formación de Profesorado Universitario”) from the Spanish Ministry of Science, Innovation and Universities (Ref. FPU15/03595). The supervisors of this Thesis are Dr. Angel Ortiz, and Dra. María del Mar Alemany Diaz that are Professors in the Research Centre of Management and Production Engineering (CIGIP) of the Universitat Politècnica de València. The FPU grant has been endorsed by the supervisor Dr. Ángel Ortiz. This Thesis has also been supported by the project ‘RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems’ (Ref. 691249) funded by the EU under its funding scheme H2020-MSCA-RISE-2015, the project ‘Methods and models for operations planning and order management in supply chains characterised by uncertainty in production due to the lack of product uniformity’ (PLANGES-FHP) (Ref. DPI2011- 23597) funded by the Spanish Ministry of Economy and Competitiveness. The projects RUC-APS and PLANGES-FHP have been led by the one of the supervisors of this Thesis Dr. María del Mar Eva Alemany. In order to obtain the international mention for this Thesis, three months of research stages have been made in the research agency Agenzia Lucana di Sviluppo e di Innovazione in Agricoltora, located in Metaponto (Italy)
Esteso Álvarez, A. (2020). Operations research models for the management of supply chains of perishable and heterogeneous products in uncertain contexts. Application to the agri-food and ceramic sectors [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/141099
TESIS
Compendio

The exponential development of biotechnology has lead to a quasi unlimited number of potential products going from biopolymers to vaccines. Cell culture has therefore evolved from the simple cell growth outside its natural environment to its use to produce molecules that they do not naturally produce. This rapid development could not be continued without new control and supervising tools as well as a good process understanding. This requirement involves however a large diversity and a better accessibility of process measurements. In this framework, software sensors show numerous potentialities. The objective of a software sensor is indeed to provide an estimation of the system state variables and particularly those which are not obtained through in situ hardware sensors or laborious and expensive analysis. In this context, This work attempts to join the knowledge of increasing bioprocess complexity and diversity and the time scale of process developments and favours systematic modelling methodology, its flexibility and the speed of development. In the field of state observation, an important modelling constraint is the one induced by the selection of the state to estimate and the available measurements. Another important constraint is the model quality. The central axe of this work is to provide solutions in order to reduce the weight of these constraints to software sensors development. On this purpose, we propose four solutions to four main questions that may arise. The first two ones concern modelling uncertainties.

1."How to develop a software sensor using measurements easily available on pilot scale bioreactor?" The proposed solution is a static software sensor using an artificial neural network. Following this modelling methodology we developed static software sensors for the biomass and ethanol concentrations in a pilot scale S. cerevisae cell culture using the measurement of titrating base quantity, agitation rate and CO&
Doctorat en sciences agronomiques et ingénierie biologique
info:eu-repo/semantics/nonPublished

Commercialisées depuis 1996, les plantes génétiquement modifiées produisant une toxine insecticide (toxine Cry) dérivée de Bacillus thuringiensis et appelées plantes Bt ciblent certains Lépidoptères ou Coléoptères ravageurs. Au fil des ans, les surfaces cultivées en plantes Bt sont de plus en plus importantes et contrôlent de larges populations d'insectes. Pour limiter le risque de développement de populations résistantes, une stratégie agricole appelée 'Haute Dose / Zone Refuge' est actuellement recommandée aux Etats-Unis par l'Environmental Protection Agency. Cette stratégie préventive nécessite la plantation d'une 'zone refuge' composée de plantes non-Bt utilisables par le ravageur ciblé et plantée à proximité de la 'zone Bt' qui synthétise une haute dose de toxine Cry.

Mon projet de recherche s’inscrit dans le cadre de l’évaluation de l'efficacité de cette stratégie et s’articule en deux phases :une phase expérimentale et une phase théorique. La première se concentre sur la caractérisation en laboratoire de l'impact des toxines Cry sur la biologie d'un ravageur. Cette phase constitue un support au volet théorique :la mise au point d’un modèle mathématique évaluant l'efficacité de la stratégie HD/R. L'originalité de ce projet repose entre autre sur l'interactivité entre ces deux volets.

Volet expérimental. Impact des toxines Cry sur la biologie de Plodia interpunctella. Nous évaluons séparément l'impact d'une gamme de concentrations de deux toxines Cry (CryXX et CryYY) sur une série de paramètres comportementaux et biologiques d'un insecte commun des denrées stockées: Plodia interpunctella (Hübner) (Lepidoptera :Pyralidae). Ces paramètres sont sélectionnés car leur variation pourrait avoir un impact sur l'efficacité de la stratégie HD/R dans le contrôle de la résistance. Il est donc pertinent de les quantifier pour intégrer dans le modèle des ordres de grandeur réalistes et générer des résultats qui ne sont pas uniquement basés sur des spéculations théoriques.

Volet théorique A. Efficacité de la stratégie HD/R pour des plantes Bt synthétisant une ou deux toxines simultanément. La stratégie 'HD/R' a été développée pour prévenir la résistance envers les plantes Bt synthétisant une seule toxine. Or, depuis 2003, de nouvelles variétés de coton Bt synthétisant simultanément deux toxines Cry sont commercialisées (BollgardII® et WidestrikeTM). Nous évaluons, grâce au modèle que nous avons développé, l'efficacité de cette stratégie lors d'une utilisation exclusive de plantes Bt synthétisant une ou deux toxines.

Volet théorique B. Impact du ralentissement du développement des insectes sur les plantes Bt sur l'efficacité de la stratégie HD/R. Le volet expérimental met en évidence un allongement de la durée du développement des larves se nourrissant sur une diète contaminée en toxine Cry. Ce ralentissement induit une séparation temporelle entre l'émergence des adultes de la zone Bt et de la zone refuge et perturbe une hypothèse principale de la stratégie HD/R: le croisement aléatoire entre adultes, indépendamment du génotype et de la zone d'origine. Dans ce troisième chapitre, nous étudions l'impact de la perturbation du croisement aléatoire sur l'efficacité de la stratégie HD/R. Nous testons également deux options pour optimiser la stratégie en cas d'asynchronie: l'utilisation de plantes Bt synthétisant une faible concentration en toxine (atténuant le décalage entre l'émergence des adultes) ou l'augmentation de la taille de la zone refuge (favorisant la survie des individus porteurs d'allèle de sensibilité et donc optimisant la dilution de la résistance à la génération suivante).

Ce travail s'intègre dans une problématique actuelle et utilise des outils de biologie théorique (théories de la dynamique et de la génétique des populations) ainsi que le développement d'un modèle mathématique. Il apporte des éléments de réponse et de réflexion sur l'optimisation de la gestion de la résistance des insectes mais c'est aussi une illustration de la complémentarité entre la biologie expérimentale et théorique.

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On the market since 1996, genetically modified plants synthesizing an insecticidal toxin (Cry toxin) stemmed from Bacillus thuringiensis, called Bt plants, target several insect pests (Lepidoptera or Coleoptera). Bt crops cover increasingly larger areas and control important pest populations The Insect Resistance Management Strategy (IRM) strategy currently recommended in the U.S.A. to limit the development of resistant populations is the High Dose / Refuge zone (HD/R) strategy. This pre-emptive strategy requires a refuge zone composed by non-Bt plants, usable by the target insect and in close proximity of the Bt zone synthesizing a high toxin concentration.

My research project contributes to the effectiveness assessment of this HD/R strategy. It is structured on two main parts: an experimental, and a theoretical section. The first part characterizes the impact of Cry toxins on the biology of an insect pest. It is the basis of the theoretical part: the implementation of a mathematical model, which evaluates the effectiveness of the HD/R strategy.

The originality of this project is based on the interactivity of these two components.

Experimental section. Impact of the Cry toxins on the biology of Plodia interpunctella. We assess the impact of a range of concentrations of two Cry toxins (CryXX et CryYY) on several behavioural and biological parameters of a common pest of stored products: Plodia interpunctella (Hübner) (Lepidoptera :Pyralidae). These parameters are selected because their variation could influence the effectiveness of a HD/R strategy. So, it is important to quantify these parameters so that realistic values can be integrated in our model. The results of the model are thus not based on theoretical assumptions alone.

Theoretical section A. Effectiveness of a HD/R strategy with Bt plants synthesizing one or two toxins. Initially, the HD/R strategy has been developed to limit the resistance towards Bt plants synthesizing one toxin. However, since 2003, new Bt cotton varieties synthesize two toxins simultaneously (BollgardII® et WidestrikeTM). We assess, with our model, the effectiveness of this strategy for Bt plants synthesizing one or two toxins.

Theoretical section B. Impact of the slowing down of the insect development reared on Bt plants on the effectiveness of the HD/R strategy. The experimental part demonstrates that larvae reared on a Bt diet have a protracted development duration. The consequence of this is a temporal separation between adult emergence in the two zones (Bt zone and refuge zone). This could affect the main assumption of the HD/R strategy, i. e. random mating independently of the genotype and of the native zone. In this third chapter, we study the impact of random mating disruption on the effectiveness of a HD/R strategy. We test two options to optimise the strategy in case of asynchrony: the use of Bt plants synthesizing a lower toxin concentration (limiting emergence asynchrony) or increasing the refuge zone size (favouring the survival of insect carrying one or two susceptible allele and thus optimising the dilution of resistance at the next generation).

This work is applied to a current issue. It uses some of the tools of theoretical biology (theories of population dynamics and population genetics) and develops a mathematical model. It provides some responses and some elements of thought about insect resistance management. It is also an illustration of the complementarity between experimental and theoretical biology.

Doctorat en Sciences
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This dissertation presents several methods for improving statistical and first principles modeling capabilities, with an emphasis on nonlinear, unsteady state batch processes. Batch process online monitoring is chosen as a main research area here due to its importance from both theoretical and practical points of view. Theoretical background and recent developments of PCA/PLS-based online monitoring methodologies are reviewed, along with fault detection metrics, and algorithm variations for different applications. The available commercial softwares are also evaluated based on the corresponding application area. A detailed Multiway PCA based batch online monitoring procedure is used as the starting point for further improvements. The issue of dynamic batch profile synchronization is addressed. By converting synchronization into a dynamic optimization problem, Dynamic Time Warping (DTW) and Derivative DTW (DDTW) show the best performance by far. To deal with the singularity point and numerical derivative estimation problems of DTW and DDTW in the presence of noise, a robust DDTW algorithm is proposed by combining Savitzky-Golay filter and DDTW algorithm together. A comparative analysis of robust DDTW and available methods is performed on simulated and real chemical plant data. As traditional Multiway PCA-based (MPCA) methods consider batch monitoring in a static fashion (fail to consider time dependency between/within process variables with respect to time), an EWMA filtered Hybrid-wise unfolding MPCA (E-HMPCA) is proposed that considers batch dynamics in the model and reduce the number of Type I and II errors in online monitoring. Chemical and biochemical batch examples are used to compare the E-HMPCA algorithm with traditional methods. First principles modeling is known to be time consuming for development. In order to increase modeling efficiency, dynamic Design of Experiments (DOE) is introduced for Dynamic Algebraic Equation (DAE) system parameter estimation. A new criterion is proposed by combining PCA and parameter sensitivity analysis (P-optimal criterion). The new criterion under certain assumptions reduce to several available criteria and is suitable for designing experiments to improve estimation of specific parameter sets. Furthermore, the criterion systematically decomposes a complex system into small pieces according to PCA. Two engineering examples (one batch, one continuous) are used to illustrate the idea and algorithm.
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