This research deals with the modeling and control of a plasticating twin screw extruder (TSE) that will be used to obtain consistent product quality. The TSE is a widely used process technology for compounding raw polymers. Compounding creates a polymer with improved properties that satisfy the demand of modern plastic applications. Modeling and control of a TSE is challenging because of its high nonlinearity, inherent time delay, and multiple interactive dynamic behavior. A complete methodology is proposed in this thesis to design an advanced control scheme for a TSE. This methodology was used to develop a model predictive control scheme for a laboratory scale plasticating TSE and to implement the control scheme in real-time. The TSE has a processing length of 925 mm and a length to screw diameter ratio (L/D) of 37. High density polyethylenes with different melt indices were used as processing materials. Manipulated variables and disturbance variables were selected based on knowledge of the process. Controlled variables were selected using a selection method that includes a steady state correlation between process output variables and product quality variables, and dynamic considerations. Two process output variables, melt temperature (Tm) at the die and melt pressure (Pm) at the die, were selected as controlled variables. A new modeling approach was proposed to develop grey box models based on excitation in the extruder screw speed (N), one of the manipulated variables. The extruder was excited using a predesigned random binary sequence (RBS) type excitation in N and nonlinear models relating Tm and Pm to N were developed using this approach. System identification techniques were used to obtain model parameters. The obtained models have an autoregressive moving average with exogenous (ARMAX) input structure and the models explain the physics of the extrusion process successfully. The TSE was also excited using a predesigned RBS in the feed rate (F) as a manipulated variable. Models relating Tm and Pm to F were developed using a classical system identification technique; both models have ARMAX structures. The model between Pm and F was found to give excellent prediction for data obtained from a stair type excitation, indicating that the obtained models provide a good representation of the dynamics of the twin screw extruder. Analysis of the TSE open loop process indicated two manipulated variables, N and F, and two controlled variables, Tm and Pm. Thus, a model predictive controller (MPC) was designed using the developed models for this 2X2 system and implemented in real-time. The performance of the MPC was studied by checking its set-point tracking ability. The robustness of the MPC was also examined by imposing external disturbances. Finally, a multimodel operating regime was used to model Tm and N. The operating regime was divided based on the screw speed, N. Local models were developed using system identification techniques. The global model was developed by combining local models using fuzzy logic methodology. Simulated results showed excellent response of Tm for a wide operating range. A similar approach was used to design a global nonlinear proportional-integral controller (n-PI) and a nonlinear MPC (n-MPC). Both the controllers showed good set-points tracking ability over the operating range. The multiple model-based MPC showed smooth transitions from one operating regime to another operating regime. / Process Control

The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or model structure. Dealing with a set of performance measures evaluated at a high temporal resolution implies analyzing and interpreting a high dimensional data set. This paper presents a method for such a hydrological model performance assessment with a high temporal resolution and illustrates its application for two very different rainfall-runoff modeling case studies. The first is the Wilde Weisseritz case study, a headwater catchment in the eastern Ore Mountains, simulated with the conceptual model WaSiM-ETH. The second is the Malalcahuello case study, a headwater catchment in the Chilean Andes, simulated with the physicsbased model Catflow. The proposed time-resolved performance assessment starts with the computation of a large set of classically used performance measures for a moving window. The key of the developed approach is a data-reduction method based on self-organizing maps (SOMs) and cluster analysis to classify the high-dimensional performance matrix. Synthetic peak errors are used to interpret the resulting error classes. The final outcome of the proposed method is a time series of the occurrence of dominant error types. For the two case studies analyzed here, 6 such error types have been identified. They show clear temporal patterns, which can lead to the identification of model structural errors.

No description available.

A presente proposta de estudo refere-se à identificação de modelo linear empírico para processo de transferência de oxigênio das bolhas de ar para o meio líquido, simulação para testes de controle e implementação de uma estratégia de controle em escala laboratorial em tempo real. Os ensaios de controle foram na unidade experimental (canal aberto) existente no laboratório de hidráulica ambiental o qual foi adaptado para aeração com sensores, atuadores, microcomputador, interface AD/DA. Foi testado o algoritmo de controle do tipo convencional PID (Proportional Integral Derivative control). Com os resultados obtidos da perturbação degrau na variável de entrada (alimentação do ar) foi possível identificar o sistema como um modelo de primeira ordem, suficiente para os propósitos de controle. Baseado na identificação, foi ajustado um controlador PID para implementação experimental. A principal contribuição desta pesquisa consistiu no emprego de uma estratégia de controle adequada na prática, ao processo de aeração. / The current study refers to the identification of an empirical linear model for the oxygen transfer process from air bubbles to liquid, control tests simulation and implementation of a control strategy at real time in laboratory scale. The control tests were carried out at the experimental unit (open channel) located at the environmental hydraulic laboratory which was adapted to aeration process with sensors, actuators, microcomputer, AD/DA interface. The classic PID (Proportional Integral Derivative control) algorithm was tested. With results from step response of input variable (air feeding) it was possible to identify the system as a first order model, enough for the control purposes. Based on the identification, a PID controller was adjusted for the experimental implementation. The main contribution of this work consisted of the employment of an appropriate control strategy to the aeration process in practice.

In this thesis, identification of periodically varying orders of univariate Periodic Autoregressive Moving-Average (PARMA) processes is mainly studied. The identification of the varying orders of PARMA process is carried out by generalizing the well-known Box-Jenkins techniques to a seasonwise manner. The identification of pure periodic moving-average (PMA) and pure periodic autoregressive (PAR) models are considered only. For PARMA model identification, the Periodic Autocorrelation Function (PeACF) and Periodic Partial Autocorrelation Function (PePACF), which play the same role as their ARMA counterparts, are employed. For parameter estimation, which is considered only to refine model identification, the conditional least squares estimation (LSE) method is used which is applicable to PAR models. Estimation becomes very complicated, difficult and may give unsatisfactory results when a moving-average (MA) component exists in the model. On account of overcoming this difficulty, seasons following PMA processes are tried to be modeled as PAR processes with reasonable orders in order to employ LSE. Diagnostic checking, through residuals of the fitted model, is also performed stating its reasons and methods. The last part of the study demonstrates application of identification techniques through analysis of two seasonal hydrologic time series, which consist of average monthly streamflows. For this purpose, computer programs were developed specially for PARMA model identification.

Made available in DSpace on 2014-12-17T15:01:20Z (GMT). No. of bitstreams: 1 BriggidaDM.pdf: 1596693 bytes, checksum: 9715f450449b483eb851c1d730270c57 (MD5) Previous issue date: 2009-08-28 / The rotary dryer is one of the most used equipments in processing industries. Its automatic control mode of operation is important specially to keep the moisture content of the final product in the desired value. The classical control strategies, like PID (proportional integral derivative) control, are largely used in the industrial sector because of its robustness and because they are easy to be implemented. In this work, a data acquisition system was implemented for monitoring the most relevant process variables, like: both inlet and outlet drying air temperature, dryer rotation, outlet air speed and humidity, and mass of the final product. Openloop tests were realized to identify a mathematical model able to represent the drying process for the rotary system. From this model, a PID controller was tuned using a direct synthesis method, assuming a first order trajectory. The PID controller was implemented in the system in order to control the inlet drying air temperature. By the end, closedloop tests (operating in automatic mode) were realized to observe the controller performance, and, after setting the best tune, experiments were realized using passion fruit seeds as raw material. The experiments realized in closedloop showed a satisfactory performance by the implemented control strategy for the drying air temperature of the rotary system / O secador rotat?rio ? um dos equipamentos amplamente utilizados nas ind?strias de processamento. Sua opera??o em modo de controle autom?tico ? importante para manter, principalmente, a umidade do produto final na especifica??o de interesse. As estrat?gias de controle cl?ssicas, tais como o controle PID (proporcional integral derivativo), s?o largamente utilizadas no setor industrial devido ? sua robustez e facilidade de implementa??o. Neste trabalho foi implementado um sistema de aquisi??o de dados para o monitoramento das vari?veis mais relevantes do processo de secagem, tais como: temperatura do g?s na entrada e na sa?da do secador, rota??o do tambor, velocidade e umidade do ar na sa?da do secador, e massa do produto final. Testes em malha aberta foram realizados para identificar um modelo matem?tico capaz de representar o processo de secagem no sistema rotat?rio. A partir deste modelo, o controlador PID foi sintonizado utilizando o m?todo de s?ntese direta e admitindo uma trajet?ria de primeira ordem. O controlador PID foi implementado no sistema com o objetivo de controlar a temperatura do ar de secagem na alimenta??o do secador. Por fim, testes em malha fechada (operando em modo autom?tico) foram realizados para observar o desempenho do controlador e, com a melhor sintonia definida, experimentos com a mat?riaprima, rejeito de maracuj?, se procederam. Os ensaios realizados em malha fechada permitiram verificar um desempenho satisfat?rio da estrat?gia de controle implementada para a temperatura do ar de secagem do sistema rotat?rio

A presente proposta de estudo refere-se à identificação de modelo linear empírico para processo de transferência de oxigênio das bolhas de ar para o meio líquido, simulação para testes de controle e implementação de uma estratégia de controle em escala laboratorial em tempo real. Os ensaios de controle foram na unidade experimental (canal aberto) existente no laboratório de hidráulica ambiental o qual foi adaptado para aeração com sensores, atuadores, microcomputador, interface AD/DA. Foi testado o algoritmo de controle do tipo convencional PID (Proportional Integral Derivative control). Com os resultados obtidos da perturbação degrau na variável de entrada (alimentação do ar) foi possível identificar o sistema como um modelo de primeira ordem, suficiente para os propósitos de controle. Baseado na identificação, foi ajustado um controlador PID para implementação experimental. A principal contribuição desta pesquisa consistiu no emprego de uma estratégia de controle adequada na prática, ao processo de aeração. / The current study refers to the identification of an empirical linear model for the oxygen transfer process from air bubbles to liquid, control tests simulation and implementation of a control strategy at real time in laboratory scale. The control tests were carried out at the experimental unit (open channel) located at the environmental hydraulic laboratory which was adapted to aeration process with sensors, actuators, microcomputer, AD/DA interface. The classic PID (Proportional Integral Derivative control) algorithm was tested. With results from step response of input variable (air feeding) it was possible to identify the system as a first order model, enough for the control purposes. Based on the identification, a PID controller was adjusted for the experimental implementation. The main contribution of this work consisted of the employment of an appropriate control strategy to the aeration process in practice.

This dissertation deals with identification, classification and efficiency assessment in general and is later on applied to Wüstenrot - Building and Loan Association, a.s. Process is the core unit of the procedural type of Organization Management. Therefore, the Building and Loan Asociation defines the key processes and proceeds to the process mapping at the selected detail level. In the first place, this concerns the corporational detail level. Secondly, processes of Customer Satisfication are elaborated. These processes make a synergic effect and cause most valuable benefits providing the fact they are controlled. This means the Corporation Management has to reflect to the outcomes of the Process Efficiency Assessment. Every single process is described from the current situation point of view. Subsequently, proposals are made to improve its efficiency assessment.

<p>Owing to the rise in fossil fuel prices, overall energy security concerns, and the current push towards green engineering; renewable and green fuels have seen an increase in interest in recent years. Two notable technologies in this green movement are the production of biodiesel from microalgae and the production of biogas from anaerobic digestion of waste biomass. Production of biodiesel from microalgae was studied extensively in the 80s through the early 90s and found to be economically infeasible given the technology of the time. However, recent literature has suggested that one possible method to improve the feasability of the process would be to combine it with an anaerobic digestor to provide nutrient and biomass recycling. For such a system, having accurate models of each process would be highly advantageous for optimal design and control. To this end this thesis moves towards this overall goal by examining and modelling the anaerobic digestion of the microalgae <em>Chlorella vulgaris</em>.</p> <p>Starting with a set of experimental data (anaerobic digestion of <em>Chlorella vulgaris</em>) provided by LBE-INRA, the minimum number of kinetic equations needed to predict the data are found using principal component style analysis. This number is found to be two to three reactions. Using this as a basis for model development, a mass balance model is developed around both two and three reaction cases. To date there is very little literature on the modelling of anaerobic digestion of microalgae and so kinetic laws are selected from the general anaerobic digestion models ``Anaerobic Digestor Model 1'' (ADM1) and ``Acidogenesis/Methanogenisis Model'' (AM2). Given that the kinetic laws were derived from general literature, model fitting is a must. To faciliate this process a novel systematic parameter identification procedure to locate identifiable parameter subsets within each model is presented. Applying this novel procedure to the provided data is seen to lead to promising identification results. Through these identification trials it is shown that the three reaction model best captures the dynamics of the system. This three reaction model serves as the basis for subsequent steady state optimality and sensitivity analysis. From these efforts it is shown that the predicted optimal curves match literature data very well but uncertainty in certain key parameter estimates lead to highly sensitive model predictions (and therefore low confidence). This leads to the conclusion that the developed model is capable of predicting the kinetics of <em>Chlorella</em> digestion but additional trials are needed to further refine the model fitting results.</p> <p>Coupling an anaerobic digester to a microalgal culture is currently considered one of the most promising avenues towards the production of renewable bioenergy, either in the form of biodiesel or biogas. Accurate mathematical models are crucial tools to assess the potential of such coupled biotechnological processes and help optimize their design, operation and control. This paper focuses on the compartment of anaerobic digestion of microalgae. Using experimental data for the anaerobic digestion of <em>Chlorella vulgaris</em>, a grey-box model is developed that allows good prediction capabilities and retains low complexity. The proposed methodology proceeds in two steps, namely a structural and a parametric identification steps. The fitted model is then used to conduct preliminary optimization for the production of biogas from <em>Chlorella vulgaris</em>. The results provide some insight into the potential for bioenergy production from the digestion of microalgae and, more generally, the coupled process.</p> / Master of Applied Science (MASc)

Le travail présenté dans cette thèse concerne la modélisation et la commande robuste en force de robots manipulateurs industriels à articulations flexibles utilisés pour le procédé FSW. Afin de réduire les temps de calcul et l'occupation de la mémoire, une approche basée sur la méthode par intervalle est proposée en vue de la simplification des modèles dynamiques des robots industriels, et contribue à identifier les paramètres d'inertie qui sont négligeables. Des études de cas sur trois types de trajectoires de test et l’analyse des couples moteurs ont démontré l'efficacité et les bonnes performances de la méthode de simplification. Ensuite, la modélisation dynamique et l'identification des paramètres du procédé FSW ont été effectuées. Les paramètres des modèles linéaires et non-linéaires de forces axiales sont identifiés. Sur la base de la modélisation du procédé FSW qui considère simultanément la cinématique du système complet, le modèle de déplacement du robot rigide, les flexibilités des articulations et le modèle dynamique de la force axiale, un contrôleur robuste en force est obtenu par la méthode de réglage fréquentielle. En outre, un simulateur du procédé FSW robotique est développé et les résultats de simulation montrent les bonnes performances du contrôleur en force. L'oscillation de la force axiale dans le procédé FSW peut être simulée en utilisant un modèle de perturbation de la position verticale de référence. / The work presented in this thesis focuses on the modeling and robust force control of flexible joints industrial robot manipulators used for FSW process. In order to reduce computation time and memory occupation, a novel interval-based approach for dynamic model simplification of industrial robots is proposed, which applies to arbitrary trajectories of whole robot workspace and contributes to obtaining negligible inertia parameters. Cases studies have been carried out on three kinds of test trajectories and torques analysis of robot dynamic equation, demonstrating the effectiveness and good performance of the simplification method. Then, the dynamic modeling and identification of robotic FSW process is performed, and the parameters of linear and nonlinear dynamic axial force process models are identified by using the plunge depth and its derivative. On the basis of the modeling of robotic FSW process which simultaneously considers the complete kinematics, the rigid robot displacement model, the joint flexibility and the dynamic axial force process model, a robust force controller can be obtained by using the frequency response approach. Besides, a simulator of robotic FSW process is developed and simulation results show good performance of the force controller. The oscillation of axial force in FSW process can be simulated when a disturbance model of initial vertical reference position is proposed and used in the simulation.