Dissertations / Theses on the topic 'Plant model with time delays'

This thesis deals with model predictive control principally Based Predictive Control (MPC). The first part describes the principle of predictive control, cost function, the choice of a constraints in regulation and the choice of weights. In the next section is an analysis system: a system with non-minimal phase (control water turbine), oscillating systems (trolley frame control) and system with a time-delay . In all of these systems is performed classical feedback control using PID control and concurrently regulation with the MPC. MPC is selected as the solution fy Mathworks Model Predictive Control Toolbox and Simulink. The results are then analyzed using the criteria of quality control.

The chemical processes used to manufacture pulp are always in development to cope with increasing environmental demands and competition. With a deeper understanding of the processes, the pulping industry can become both more profitable and effective at keeping an even and good quality of pulp, while reducing emissions. One step in this direction is to more accurately determine the time delay for a process, defined as the time it takes for a change in input to affect the process’s output. This information can then be used to control the process more efficiently. The methods used today to estimate the time delay use simple models and assumptions of the processes, for example that that the pulp behaves like a ”plug” that never changes its shape throughout the process. The problem with these assumptions is that they are only valid under ideal circumstances where there are no disturbances. This Master’s thesis aims to investigate if it is possible to measure the process time delay using only the input and output data from the process, and see if this estimation is more accurate than the existing model based methods. Another aim is to investigate if the process time delay can be monitored in real time. We investigated three methods: cross-correlation applied to the raw input and output data, cross-correlation applied to the derivative of the input and output data, and a convolutional neural network trained to identify the process time delay from the input and output data. The results show that it is possible to find the time delay, but with significant deviations from the models used today. Due to a lack of data where the time delay was measured, the reason for this deviation requires more research. The results also show that the three methods are unsuitable for real-time estimation. However, the models can likely monitor how the process time delay develops over long periods.

El alto grado de automatización adquirido en las plantas químicas durante las últimas décadas hace que las tareas de supervisión sean ahora más complejas y delicadas. Esta supervisión requiere de sistemas y herramientas sofisticadas que puedan sacar provecho de los módulos de adquisición de información instalados en planta. Así, el preciso seguimiento de las variables de proceso o la fácil operatividad de los procesos, gracias a los sistemas de control regulatorio actuales, son aspectos relevantes que deben ser contemplados a la hora de dar una respuesta global a las desviaciones del régimen normal de operación.
Esta tesis presenta un enfoque global para la gestión de situaciones anormales en plantas químicas. En esta propuesta se contempla el flujo completo de información requerido para responder efectivamente a cualquier situación anormal que se pueda presentar. Mediante esta visión global, primeramente se identifican todos los módulos de planta involucrados en la gestión de fallos; luego se focalizan esfuerzos en mejorar las técnicas que estos módulos usan para su operación; por último, se aprovechan algunas de las sinergias descubiertas mediante esta visión global de la gestión de eventos anormales.
De esta forma, el primer capítulo esetablece un primer acercamiento general a las motivaciones y ámbito de las tesis, describiendo rasgos fundamentales en la evolución de la industria química durante los últimos años y los requerimientos asociados al nuevo modelo de supervisión. El segundo capítulo resume las técnicas y aplicaciones actuales para reducir el riesgo de incidencias y accidentes en procesos químicos. Este resumen se centra principalmente en aquellas metodologías más empleadas en la literatura y aquellas con más aceptación en ambientes industriales. Una vez analizado el estado del arte en la supervisión de procesos, se propone un enfoque global de gestión de eventos anormales en el tercer capítulo, que presenta los eslabones de la cadena de gestión de eventos anormales, los cuales serán abordados en detalle en los capítulos restantes.
De esta forma, el capítulo 4 se centra en la mejora de los sistemas de adquisición de datos y su posterior tratamiento mediante reconciliación con modelos del proceso. Los capítulos 5, 6, 7 y 8 se dedican al estudio de la parte central de cualquier sistema de respuesta a eventos anormales, el módulo de diagnóstico. El capítulo 5 formaliza el problema de diagnosis y estandariza los índices de evaluación de funcionamiento de los sistemas de diagnóstico. Los capítulo 6 y 7 preentan dos nuevos sistemas de diagnosis basados en el uso de datos históricos. El primero desarrollado en el capítulo 6, implementa un algoritmo de aprendizaje llamada "Máquinas de soporte vectorial" (SVM) adoptando un enfoque "MultiEtiqueta" que permite el diagnóstico eficaz de fallos simultáneos. El segundo sistema (capítulo 7) integra un módulo de detección basado en un modelo de Análisis de Componentes Principales y un módulo de diagnóstico basado en reglas "si-entonces". Como compendio de la diagnosis, el capítulo 8 estudia las fuerzas y debilidades de los sistemas de diagnóstico propuestos y propone una integración de módulos de diagnóstico complementarios que supera el rendimiento de cualquiera de los sistemas por separado.
Los capítulos 9 y 10 están centrados en la toma efectiva de decisiones frente a desviaciones del régimen normal de operación. El capítulo 9 presenta una metodología novedosa de integración de conocimiento del proceso en línea y fuera de línea, que permite generar información sustancial de soporte al operador en la toma de decisiones. El capítulo 10 se centra también en la toma de decisiones, mostrando las sinergias generadas al integrar el sistema de diagnosis con otros módulos de planta. En este capítulo el sistema global de gestión de eventos anormales es complementado con un módulo de optimización en línea. De esta forma el nuevo soporte a la toma de decisiones frente a perturbaciones no sólo tiene en cuenta aspectos relacionados con la seguridad sino también con la economía de la planta. Además, la integración permite que la técnica de optimizaicón empleada sea más fiable en su aplicación.
Todos los capítulos incluyen una primera parte teórica seguida de una segunda parte centrada en la validación académica e industrail. Aquellos temas que exceden el alcance de estas tesis, son comentados y propuestos como trabajo futuro en el capítulo 11.
The hight automation acquired in chemical industry during last decades has made supervision a delicate and complex task. Therefore, current plants supervision require of sophisticated systems and tools that can create profit from the information installed modules. Thus, the precise tracking of process variables or the high plant operability, achieved by the current regulatory control, are aspects that must be contemplated when the plant has to give a global response against deviations from normal operating regime.
This thesis presents a global approach for the management of abnormal situations in chemical plants. In this proposal the complete flow of information required to respond to any nonstandard situation is considered. This global approach incorporates several key aspects: first, all the plant modules that are necessary in the faults management are presented; secondly, this thesis focuses on improving the techniques used in each of these modules so far. Lastly, synergies discovered by the proposed global approach are used to develop novel and promising solutions to address process safety and optimization difficulties.

A prominent feature of the dynamics of large neuronal networks are the synchrony-driven collective oscillations generated by the interplay between synaptic coupling and synaptic delays. This thesis investigates the emergence of delay-induced oscillations in networks of heterogeneous spiking neurons. Building on recent theoretical advances in exact mean field reductions for neuronal networks, this work explores the dynamics and bifurcations of an exact firing rate model with various forms of synaptic delays. In parallel, the results obtained using the novel firing rate model are compared with extensive numerical simulations of large networks of spiking neurons, which confirm the existence of numerous synchrony-based oscillatory states. Some of these states are novel and display complex forms of partial synchronization and collective chaos. Given the well-known limitation of traditional firing rate models to describe synchrony-based oscillations, previous studies greatly overlooked many of the oscillatory states found here. Therefore, this thesis provides a unique exploration of the oscillatory scenarios found in neuronal networks due to the presence of delays, and may substantially extend the mathematical tools available for modeling the plethora of oscillations detected in electrical recordings of brain activity.
Una característica fonamental de la dinàmica d'una xarxa neuronal és l'emergència d'oscil·lacions degudes a sincronització. L'origen d'aquestes oscil·lacions és molt sovint degut les interaccions sinàptiques i als seus retards temporals inherents. Aquesta tesi analitza la emergència d'oscil·lacions produïdes per retards sinàptics en xarxes neuronals heterogènies. A partir de troballes recents en teories de camp mig per xarxes neuronals, aquest treball explora la dinàmica i les bifurcacions d'un model de {\it rate} amb diferents tipus de retards sinàptics. En paral·lel els resultats obtinguts mitjançant el nou model de rate són comparats amb simulacions numèriques de grans xarxes neuronals. Aquestes simulacions confirmen l'existència de nombrosos estats oscil·latoris produïts per sincronització. Alguns d'aquests estats són nous I mostren formes complexes de sincronització parcial i de caos col·lectiu. Gran part d'aquestes oscil·lacions han estat àmpliament ignorades a la literatura, degut a la limitació dels models tradicionals de rate per descriure estats amb un alt nivell de sincronització. Així doncs aquesta tesi ofereix una exploració única dels possibles escenaris oscil·latoris en xarxes neuronals amb retards sinàptics, i amplia significativament les eines matemàtiques disponibles per a la modelització de la gran diversitat d'oscil·lacions neuronals presents en les mesures elèctriques de l'activitat cerebral.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
This study proposes a production model that increases the manufacturing capacity in a small and medium-sized enterprise (SME) of garments with an aim to reduce the nonfulfillment of order deliveries. An assessment has been done and waiting times between production processes have been identified, along with defective products and inefficient work methods. This study proposes the design of a lean manufacturing model under the change management approach, whose methodology comprises five phases. In phase 0, awareness and training sessions are conducted (change management). Then, phase 1 reorganizes the work area (plant layout re-distribution and 5S) and phase 2 seeks better workload balances (line balance and Heijunka implementation). Later, phase 3 standardizes work methods (standardization). Finally, the proposed model will be validated to determine whether the selected operating tools are supported by the awareness that contributes to increasing production. © 2021, Springer Nature Switzerland AG.
Revisión por pares

The need to save energy, cut costs, and increase profit margin in process manufactureincreases continually. There is also a global drive to reduce energy use and cut down co2 emission and combat climate change. These in turn have led to more stringent requirements on process control performance. Hence, the requirements for modern systems are often not achievable using classical control techniques. Therefore, advanced control strategies are often required to ensure optimal process performance. Despite these challenges, PID has continued to be the dominant industrial control scheme. However, for systems with complex dynamics and/or high performance requirements, PID control may not be sufficient. Therefore, a significant number of industrial control loops are not performing optimally and more advanced control than PID may be required in order to achieve optimal performance. MPC is one of the advanced control schemes that has had a significant impact in the industry. Despite the benefits associated with the implementation of MPC, the technology has remained a niche application in process manufacture. This thesis seeks to address these issues by developing ways that could lead to widespread application of MPC. In the first part of this thesis, a study was carried out to understand the characteristics of processes that would benefit from the application of MPC at the regulatory control level even in the single-input single-output (SISO) case. This is a departure from the common practice in which MPC is applied at the supervisory control layer delivering set points to PID controllers at the regulatory control layer. Both numerical simulation and industrial studies were used to show and quantify benefits of MPC for SISO applications at the regulatory control layer. Some issues that have led to the limited application of MPC include the cost and human efforts associated with modelling and controller design. And to achieve high process performance, accurate models are required. To address this issue, in the second part of this thesis, a novel technique for designing MPC from routine plant data – routine data MPC (RMPC) is proposed. The proposed technique was successfully implemented on process models. This technique would reduce the high human cost associated with MPC deployment, which could make it a widespread rather than niche application in the process manufacturing industry.

Knowledge of relationships between nutrient levels, yield, maturity, and environmental influences on alfalfa (Medicago sativa L.) are necessary to estimate when to harvest alfalfa to maximize quality and yield. Objectives were to document the change in nutrient content, yield, and growth stage of alfalfa grown in Utah as it matures and to develop a simple model to predict optimal harvest date. The study involved three locations in major alfalfa producing regions in Utah. Samples were collected from three commonly grown alfalfa varieties between 26 April and 26 September in 1987. Maximum and minimum levels of crude protein (CP) observed were 32.8% to 16.2%, acid detergent fiber (ADF) 39.4% to 14.0%, and dry matter (OM) 31.7% to 14.3%. Maximum yield of 7.0 Mg ha-1 for a single harvest was observed. The growth stage and average yield in Mg ha-1 for all varieties and harvests collected were: prebud 3.6; midbud 4.2; and late bud to early bloom 4.9. As alfalfa matured CP% declined, ADF% increased, and DM% increased. Criteria used to estimate optimal harvest date was achieving not less than 20.0% CP, at least 29.0% ADF, but not more than 31.0% ADF. The estimated optimal harvest date was determined 63.3% of the time by not exceeding 31.0% ADF. Early to midbud were characteristic growth stages of the estimated optimal harvest date occurring 34.4% and 41.0% respectively. Midbud stage was characterized by elongation of the peduncle at second and third axillary bud positions. Accumulated growing degree hours (AGDH) were calculated using the ASYMCUR modeling concept. Height models were developed by averaging AGDH at 5 cm increments of shoot height. Models developed from the Nephi site were used to predict data from other sites. These models made about 37% acceptable predictions ranging from 0-100%. The general model made 23% acceptable predictions, variety models 47%, harvest models 43%, and 36% from specific data models. The general model, with a coefficient of variation (CV) of 14.6%, made fewer acceptable predictions than specific models having CV of 11.1% and 6.0%. Height models generated using the ASYMCUR concept were inefficient in predicting growth of alfalfa. This may be due to inaccurate estimates of when regrowth began, inaccurate weather data, and a variety of temperature related stresses which reduces the growth rate of alfalfa per unit of growing degree hours. Development of stress factor in cosine equations, improved data collection, and additional model generation and testing, could reduce variability and increasing percentage of acceptable predictions.

Millions are spent managing invasive weeds on public lands each year. Wildland invasive weed treatment bids are based primarily on acreage or hours but can be influenced by variables that increase treatment time and cost. Often neither the agency contracting the treatment nor the contractor has a clear idea of the amount of time that will be involved based on these variables. This makes it difficult to develop an accurate budget or bid for invasive weed control projects. It also limits managers in seeking funding and justifying treatment costs. A model has been developed that can predict herbicide application time due to four variables, weed canopy cover, slope, land cover, and weed visibility. Other variables were explored. The “smart” spray wand (SSW) is a new precision tool used to develop this model. The SSW is a spray wand with an integrated GPS and a flow meter for use with any type of spray system. The wand records the GPS location, herbicide flow,application time, and associated data of each treatment spray point. This information provided necessary data for the treatment time model. Weed control total treatment time (TTot) was hypothesized to include both treatment time (Tt) and rest time (Rt). The development and benefits of a wildland weed treatment time model are discussed. An accurate treatment time model could 1) establish an accurate standard for contractors and land managers, 2) assist in planning and managing limited treatment resources, and 3) justify funding requests and expenditures. The primary influence of the model is due to weed canopy cover (p=<2.2e-16, R2=0.5607), with smaller impacts by other variables. If canopy cover, slope, land cover, and weed visibility can be obtained for a weed control project, the model can be used.

Germination rates and germination fractions of seeds can be predicted well by the hydrothermal time (HTT) model. Its four parameters hydrothermal time, minimum soil temperature, minimum soil moisture, and variation of minimum soil moisture, however, must be determined by lengthy germination experiments at combinations of several levels of soil temperature and moisture. For some applications of the HTT model it is more important to have approximate estimates for many species rather than exact values for only a few species. We suggest that minimum temperature and variation of minimum moisture can be estimated from literature data and expert knowledge. This allows to derive hydrothermal time and minimum moisture from existing data from germination experiments with one level of temperature and moisture. We applied our approach to a germination experiment comparing germination fractions of wild annual species along an aridity gradient in Israel. Using this simplified approach we estimated hydrothermal time and minimum moisture of 36 species. Comparison with exact data for three species shows that our method is a simple but effective method for obtaining parameters for the HTT model. Hydrothermal time and minimum moisture supposedly indicate climate related germination strategies. We tested whether these two parameters varied with the climate at the site where the seeds had been collected. We found no consistent variation with climate across species, suggesting that variation is more strongly controlled by site-specific factors.
Keimungsgeschwindigkeit und Anteil gekeimter Samen lassen sich gut mit dem Hydrothermalzeit-Modell bestimmen. Dessen vier Parameter Hydrothermalzeit, Mindesttemperatur, Mindestbodenfeuchte und Streuung der Mindestbodenfeuchte müssen jedoch durch aufwendige Keimungsversuche bei Kombinationen von mehreren Temperatur- und Feuchtigkeitsstufen bestimmt werden. Für manche Anwendungen des Hydrothermalzeit-Modells sind aber ungefähre Werte für viele Arten wichtiger als genaue Werte für wenige Arten. Wenn die Mindesttemperatur und die Streuung der Mindestfeuchte aus Veröffentlichungen und Expertenwissen geschätzt würde, können die Hydrothermalzeit und Mindestbodenfeuchte aus vorhandenen Daten von Keimungsversuchen mit nur einer Temperatur- und Feuchtigkeitsstufe berechnet werden. Wir haben unseren Ansatz auf einen Keimungsversuch zum Vergleich der Keimungsquote wilder einjähriger Arten entlang eines Trockenheitsgradienten in Israel angewendet. Mit diesem Ansatz bestimmten wir die Hydrothermalzeit und Mindestfeuchtigkeit von 36 Arten. Der Vergleich mit genauen Werten für drei Arten zeigt, dass mit unserem Ansatz Hydrothermalzeit-Parameter einfach und effektiv bestimmt werden können. Hydrothermalzeit und Mindestfeuchtigkeit sollten auch bestimmte klimabedingte Keimungsstrategien anzeigen. Deshalb testeten wir, ob diese zwei Parameter mit dem Klima am Ursprungsort der Samen zusammenhängen. Wir fanden jedoch keinen für alle Arten übereinstimmenden Zusammenhang, so dass die Unterschiede vermutlich stärker durch standörtliche als durch klimatische Ursachen hervorgerufen werden.

Many agricultural fields that have received long-term applications of P often contain levels of P exceeding those required for optimal crop production. Knowledge of the effect of the P remaining in the soil (residual effect) is of great importance for fertilization management. In order to characterize P forms in soils, a wide variety of methods have been proposed. The use of dialysis membrane tubes filled with hydrous ferric oxide (DMT-HFO) has recently been reported as an effective way to characterize P desorption over a long-term in laboratoty studies. However, there is little information on the relationship between kinetics of P release using this new method and plant P uptake. This method consist of a procedure of shaking a sample for a long period of time there by exploiting the whole volume of the soil which is in contrast to the actual plant mode of uptake. This method has also practical limitations in employing it for a routine soil analysis, as it is very expensive and time consuming. The objectives of this study were (i) to study the changes in labile, non-labile and residual P using successive P desorption by DMT-HFO followed by a subsequent fractionation method (combined method) (ii) to assess how the information gained from P desorption kinetic data relates to plant growth at green house and field trials (iii) to investigate the effect of varying shaking time on DMT-HFO extractable P and (iv) to propose a short cut approach to the combined method. The release kinetics of the plots from long term fertilizer trials at the University of Pretoria and Ermelo were studied. P desorption kinetics were described relatively well by a two-component first-order model (R2 = 0.947, 0.918,&0.993 for NPK, MNK,&MNPK treatments respectively). The relative contributions of both the labile pool (SPA) and the less labile pool (SPB) to the total P extracted increased with increased P supply levels. Significant correlations were observed between the rate coefficients and maize grain yield for both soil types. The correlation between the cumulative P extracted and maize yield (r = 0.997**) however was highly significant for Ermelo soils. This method was also used to determine the changes in the different P pools and to relate these P fractions with maize yield. Highly significant correlations were observed between maize grain yield and the different P fractions including total P. In both soil types the contribution of both the labile and non-labile inorganic P fractions in replenishing the solution Pi was significant where as the contributions from the organic fractions were limited. The C/HCl-Pi is the fraction that decreased most in both cases as well. Investigation was carried out to evaluate the effect of varying shaking periods on the extractable DMT-HFO-Pi for UP soils of varying P levels. Four shaking options were applied. Significant difference was observed for the treatment of high P application. Shaking option 2 seemed relatively better than the others since it showed the strongest correlation. Thus for soils with high releasing kinetics and high total P content, provided that the P release from the soil is a rate limiting step, reducing the length of shaking time could shorten the duration one needs to complete the experiment with out influencing the predicting capacity of the methodology. The other objective of this thesis was also to present a short cut method alternative to the combined fractionation method. Comparison of the sum of DMT-HFO-Pi, NaHCO3-Pi, NaOH-Pi, D/HCl-Pi and C/HCl-Pi extracted by a conventional step-by-step method with the sum of DMT-HFO-Pi and a single C/HCl-Pi extraction as a short cut approach for all extraction periods resulted in strong and significant correlations. The C/HCl-Pi fraction extracted by both methods was correlated with maize grain yield and it was found to be highly significant. This study revealed that this short cut approach could be a simplified and economically viable option to study the P dynamics of soils especially for soils where the P pool acting as a source in replenishing the labile portion of P is already identified. The method employed here therefore could act as an analytical tool to approximate successive cropping experiments carried out under green house or field condition. However, data from a wider range of soils is needed to evaluate the universality of this method. More work is also required in relating desorption indices of this method with yield parameters especially at field level.
Thesis (PhD)--University of Pretoria, 2009.
Plant Production and Soil Science
PhD
unrestricted

Arid and semi-arid rangelands are important ecosystems that are consistently degraded through disturbances such as wildfires. After such disturbances, the invasion and dominance of annual grasses, like cheatgrass (Bromus tectorum L.), can lead to an overall loss of ecosystem productivity and an increase in fire frequency. To reduce weed dominance, native and introduced perennials species are typically be seeded in the fall. High mortality is seen from these seeded plant communities due to germinated seed being exposed to freezing, drought, fungal pathogens, and other biotic and abiotic stressors during winter months. We utilized wet-thermal accumulation models to first further validate the theory that germination from seeded plant populations occurs during periods of high environmental stress, and then to establish the practicality of abscisic acid seed coatings as a technology that could circumvent winter germination and mortality. In Chapter 1, we developed an excel workbook called Auto-Germ using Visual Basic for Applications, which allows users to estimate field germination timing based on wet-thermal accumulation models and field data. We then used Auto-Germ to model seed germination timing for 10 different species, across 6 years, and 10 Artemisia-steppe sites in the Great Basin of North America. We estimated that for the majority of the species analyzed, a mid to late-winter planting was required on average for the majority of the population to germinate in the spring. This planting time would be logistically difficult for many land managers, due to freezing and/or saturated soil conditions. In Chapter 2, we utilized wet-thermal accumulation models to evaluate the use of abscisic acid (ABA) to delay germination of Pseudoroegneria spicata (Pursh) Á. Löve (perennial native bunchgrass) across 4 years and 6 Artemisia-steppe sites. Germination models estimated that ABA seed treatments typically would delay germination of fall sown seed to late winter or early spring when conditions may be more favorable for plant establishment. Based on these results, we recommend both the use of wetthermal accumulation models as a tool in educating researchers and land managers in knowing when seeding practices should occur, and the further study of ABA seed coatings as a technology that may improve plant establishment of fall sown seeds.

We consider the problem of Adaptive Control of finite-dimensional, stable, Linear Time Invariant (LTI) plants. Amongst such plants, the subclass regarding which an upper bound on the order is not known or which are known to be nonminimum phase (zeros in the unstable region) pose formidable problems in their own right. On one hand, if an upper bound on the order of the plant is not known, adaptive control usually involves some form of order estimation. On the other hand, when the plant is allowed to be either minimum phase or nonminimum phase, the adaptive control problem, as is well-known, becomes considerably-less tractable. In this study, the class of unknown plants considered is such that no information is available on the upper bound of the plant order and, further, the plant may be either minimum phase or nonminimum phase. Albeit known to be stable, such plants throw myriads of challenges in the context of adaptive control. Adaptive control involving such plants has been addressed [79] in a Model Reference Adaptive Control (MRAC) framework. There, the inputs and outputs of the unknown plant are the only quantities available by measurement in terms of which any form of modeling of the unknown plant may be made. Inputs to the reference model have been taken from certain restricted classes of bounded signals. In particular, the three classes of inputs considered are piecewise continuous bounded functions which asymptotically approach • a nonzero constant, • a sinusoid, and • a sinusoid with a nonzero shift. Moreover, the control law is such that adaptation is carried out at specific instants separated by progressively larger intervals of time. The schemes there have been proved to be e-optimal in the sense of a suitably formulated optimality criterion. If, however, the reference model inputs be extended to the class of piecewise continuous bounded functions, that would compound the complexity of the adaptive control problem. Only one attempt [78] in adaptive control in such a setting has come to our notice. The problem there has been tackled by an application of the theory of Pade Approximations to time moments of an LTI system. Based on a time moments estimation procedure, a simple adaptive scheme for Single-Input Single-Output (SISO) systems with only a cascade compensator has been reported. The first chapter is essentially meant to ensure that the problem we seek to address in the field of adaptive control indeed has scope for research. Having defined Adaptive Control, we selectively scan through the literature on LTI systems, with focus on MRAC. We look out in particular for studies involving plants of which not much is known regarding their order and systems which are possibly nonminimum phase. We found no evidence to assert that the problem of adaptive control of stable LTI systems, not necessarily minimum phase and of unknown upper bound on the order, was explored enough, save two attempts involving SISO systems. Taking absence of evidence (of in-depth study) for evidence of absence, we make a case for the problem and formally state it. We preview the thesis. We set two targets before us in Chapter 2. The first is to review one of the existing procedures attacking the problem we intend to address. Since the approach is based on the notion of time moments of an LTI system, and as we are to employ Pade Approximations as a tool, we uncover these concepts to the limited extent of our requirement. The adaptive procedure, Plant Command Modifier Scheme (PCMS) [78], for SISO plants is reported in some detail. It stands supported on an algorithm specially designed to estimate the time moments of an LTI system given no more than its input and output. Model following there has been sought to be achieved by matching the first few time moments of the reference model by the corresponding ones of the overall compensated plant. The plant time moment estimates have been taken to represent the unknown plant. The second of the goals is to analyze PCMS critically so that it may serve as a forerunner to our work. We conclude the chapter after accomplishing these goals. In Chapter 3, we devise a time moment estimator for SISO systems from a perspective which is conceptually equivalent to, yet functionally different from, that appropriated in [78]. It is a recipe to obtain estimates of time moments of a system by computing time moment estimates of system input and output signals measured up to current time. Pade approximations come by handy for this purpose. The lacunae exposed by a critical examination of PCMS in Chapter 2 guide us to progressively refine the estimator. Infirmities in the control part of PCMS too have come to light on our probing into it. A few of these will be fixed by way of fabricating two exclusively cascade compensators. We encounter some more issues, traceable to the estimator, which need redressal. Instead of directly fine-tuning the estimator itself, as is the norm, we propose the idea of 'estimating' the lopsidedness of the estimator by using it on the fully known reference model. This will enable us to effect corrections and obtain admissible estimates. Next, we explore the possibility of incorporating feedback compensation in addition to the existing cascade compensation. With output error minimization in mind, we come up with three schemes in this category. In the process, we anticipate the risk of instability due to feedback and handle it by means of an instability preventer with an inbuilt instability detector. Extensive simulations with minimum and rionminimum phase unknown plants employing the various schemes proposed are presented. A systematic study of simulation results reveals a dyad of hierarchies of progressively enhanced overall performance. One is in the sequence of the proposed schemes and the other in going for matching more and more moments. Based on our experiments we pick one of the feedback schemes as the best. Chapter 4 is conceived of as a bridge between SISO and multivariable systems. A transition from SISO to Multi-Input Multi-Output (MIMO) adaptive control is not a proposition confined to the mathematics of dimension-enhancement. A descent from the MIMO to the SISO case is expected to be relatively simple, though. So to transit as smoothly and gracefully as possible, some issues have to be placed in perspective before exploring multivariable systems. We succinctly debate on the efforts in pursuit of the exact vis-a-vis the accurate, and their implications. We then set some notations and formulate certain results which serve to unify and simplify the development in the subsequent three chapters. We list a few standard results from matrix theory which are to be of frequent use in handling multivariable systems. We derive control laws for Single-Input Multi-Output (SIMO) systems in Chapter 5. Expectedly, SIMO systems display traits of observability and uncontrollability. Results of illustrative simulations are furnished. In Chapter 6, we formulate control laws for Multi-Input Single-Output (MISO) systems. Characteristics of unobservability and controllability stand out there. We present case studies. Before actually setting foot onto MIMO systems, we venture to conjecture on what to expect there. We work out all the cascade and feedback adaptive schemes for square and nonsquare MIMO systems in Chapter 7. We show that MIMO laws when projected to MISO, SIMO and SISO cases agree with the corresponding laws in the respective cases. Thus the generality of our treatment of MIMO systems over other multivariable and scalar systems is established. We report simulations of instances depicting satisfactory performance and highlight the limitations of the schemes in tackling the family of plants of unknown upper bound on the order and possibly nonminimum phase. This forms the culmination of our exercise which took off from the reported work involving SISO systems [78]. Up to the end of the 7th chapter, we are in pursuit of solutions for the problem as general as in §1.4. For SISO systems, with input restrictions, the problem has been addressed in [79]. The laws proposed there carry out adaptation only at certain discrete instants; with respect to a suitably chosen cost, the final laws are proved to be e>optimal. In Chapter 8, aided by initial suboptimal control laws, we finally devise two algorithms with continuous-time adaptation and prove their optimality. Simulations with minimum and nonminimum phase plants reveal the effectiveness of the various laws, besides throwing light on the bootstrapping and auto-rectifying features of the algorithms. In the tail-piece, we summarize the work and wind up matters reserved for later deliberation. As we critically review the present work, we decant the take-home message. A short note on applications followed by some loud thinking as a spin-off of this report will take us to finis.

Ce travail propose de nouvelles structures de contrôle pour la téléopération bilatérale à travers des réseaux de communication non dédiés. L'enjeu est donc de concevoir et calculer des structures de commande garantissant la stabilisation et un bon degré de performance en termes de synchronisation (suivi des positions et vitesse) et de transparence (ressenti des forces) sous les retards variables et asymétriques.Nous faisons tout d'abord un tour d'horizon des recherches récentes dans le domaine des systèmes de téléopération et de leurs caractéristiques. Puis, nous considérons des modèles linéaires à plusieurs retards variables pour lesquels nous proposons une approche d'analyse de stabilité par fonctionnelles de Lyapunov-Krasovskii et contrôle robuste H [infinity symbol . Ensuite, trois structures de téléopération seront proposées en temps continu, la comparaison de ces architectures montre que, pour un retard de réseau maximum donné ou calculé, toutes garantissent un suivi de position et vitesse. Les deux dernières, qui utilisent les forces mesurées ou estimées de l'opérateur humain et de l'environnement, garantissent de plus un suivi en force. Au final, la troisième structure (avec proxy) présente la meilleure performance, même si elle demande un peu plus de calcul. Puis, afin d'analyser et d'améliorer les performances de la troisième structure pour des modèles encore plus réalistes, une étude est menée en temps discret, mais aussi sur un modèle non linéaire ou non stationnaire sous perturbations bornées en norme. L'implantation sur la plate-forme est décrite dans un quatrième et dernier chapitre, et puis l'analyse des résultats expérimentaux est alors menée

Classically, wide-area synchronized power system monitoring has been an expensive task requiring significant investment in utility communications infrastructures for the service of relatively few costly sensors. The purpose of this research is to demonstrate the viability of power system monitoring from very low voltage levels (120 V). Challenging the accepted norms in power system monitoring, the document will present the use of inexpensive GPS time synchronized sensors in mass numbers at the distribution level. In the past, such low level monitoring has been overlooked due to a perceived imbalance between the required investment and the usefulness of the resulting deluge of information. However, distribution level monitoring offers several advantages over bulk transmission system monitoring. First, practically everyone with access to electricity also has a measurement port into the electric power system. Second, internet access and GPS availability have become pedestrian commodities providing a communications and synchronization infrastructure for the transmission of low-voltage measurements. Third, these ubiquitous measurement points exist in an interconnected fashion irrespective of utility boundaries. This work offers insight into which parameters are meaningful to monitor at the distribution level and provides applications that add unprecedented value to the data extracted from this level. System models comprising the entire Eastern Interconnection are exploited in conjunction with a bounty of distribution level measurement data for the development of wide-area disturbance detection, classification, analysis, and location routines. The main contributions of this work are fivefold: the introduction of a novel power system disturbance detection algorithm; the development of a power system oscillation damping analysis methodology; the development of several parametric and non-parametric power system disturbance location methods, new methods of power system phenomena visualization, and the proposal and mapping of an online power system event reporting scheme.
Ph. D.

Les communautés végétales constituent des systèmes complexes au sein desquels de nombreuses espèces, pouvant présenter une large variété de traits fonctionnels, interagissent entre elles et avec leur environnement. En raison de la quantité et de la diversité de ces interactions les mécanismes qui gouvernent les dynamiques des ces communautés sont encore mal connus. Les approches basées sur la modélisation permettent de relier de manière mécaniste les processus gouvernant les dynamiques des individus ou des populations aux dynamiques des communautés qu'ils forment. L'objectif de cette thèse était de développer de telles approches et de les mettre en oeuvre pour étudier les mécanismes sous-jacents aux dynamiques des communautés. Nous avons ainsi développés deux approches de modélisation. La première s'appuie sur un cadre de modélisation stochastique permettant de relier les dynamiques de populations aux dynamiques des communautés en tenant compte des interactions intra- et interspécifiques et de l'impact des variations environnementale et démographique. Cette approche peut-être aisément appliquée à des systèmes réels et permet de caractériser les populations végétales à l'aide d'un petit nombre de paramètres démographiques. Cependant nos travaux suggèrent qu'il n'existe pas de relation simple entre ces paramètres et les traits fonctionnels des espèces, qui gouvernent pourtant leur réponse aux facteurs externes. La seconde approche a été développée pour dépasser cette limite et s'appuie sur le modèle individu-centré Nemossos qui représente de manière explicite le lien entre le fonctionnement des individus et les dynamiques de la communauté qu'ils forment. Afin d'assurer un grand potentiel d'application à Nemossos, nous avons apportés une grande attention au compromis entre réalisme et coût de paramétrisation. Nemossos a ainsi pu être entièrement paramétré à partir de valeur de traits issues de la littérature , son réalisme a été démontré, et il a été utilisé pour mener des expériences de simulations numériques sur l'importance de la variabilité temporelle des conditions environnementales pour la coexistence d'espèces fonctionnellement différentes. La complémentarité des deux approches nous a permis de proposer des éléments de réponse à divers questions fondamentales de l'écologie des communautés incluant le rôle de la compétition dans les dynamiques des communautés, l'effet du filtrage environnementale sur leur composition fonctionnel ou encore les mécanismes favorisant la coexistence des espèces végétales. Ici ces approches ont été utilisées séparément mais leur couplage peut offrir des perspectives intéressantes telles que l'étude du lien entre le fonctionnement des plantes et les dynamiques des populations. Par ailleurs chacune des approches peut être utilisée dans une grande variété d'expériences de simulation susceptible d'améliorer notre compréhension des mécanismes gouvernant les communautés végétales
Plant communities are complex systems in which multiple species differing by their functional attributes interact with their environment and with each other. Because of the number and the diversity of these interactions the mechanisms that drive the dynamics of theses communities are still poorly understood. Modelling approaches enable to link in a mechanistic fashion the process driving individual plant or population dynamics to the resulting community dynamics. This PhD thesis aims at developing such approaches and to use them to investigate the mechanisms underlying community dynamics. We therefore developed two modelling approaches. The first one is based on a stochastic modelling framework allowing to link the population dynamics to the community dynamics whilst taking account of intra- and interspecific interactions as well as environmental and demographic variations. This approach is easily applicable to real systems and enables to describe the properties of plant population through a small number of demographic parameters. However our work suggests that there is no simple relationship between these parameters and plant functional traits, while they are known to drive their response to extrinsic factors. The second approach has been developed to overcome this limitation and rely on the individual-based model Nemossos that explicitly describes the link between plant functioning and community dynamics. In order to ensure that Nemossos has a large application potential, a strong emphasis has been placed on the tradeoff between realism and parametrization cost. Nemossos has then been successfully parameterized from trait values found in the literature, its realism has been demonstrated and it has been used to investigate the importance of temporal environmental variability for the coexistence of functionally differing species. The complementarity of the two approaches allows us to explore various fundamental questions of community ecology including the impact of competitive interactions on community dynamics, the effect of environmental filtering on their functional composition, or the mechanisms favoring the coexistence of plant species. In this work, the two approaches have been used separately but their coupling might offer interesting perspectives such as the investigation of the relationships between plant functioning and population dynamics. Moreover each of the approaches might be used to run various simulation experiments likely to improve our understanding of mechanisms underlying community dynamics

Vodní energie se nyní stala nejlepším zdrojem elektrické energie na zemi. Vyrábí se pomocí energie poskytované pohybem nebo pádem vody. Historie dokazuje, že náklady na tuto elektrickou energii zůstávají konstantní v průběhu celého roku. Vzhledem k mnoha výhodám, většina zemí nyní využívá vodní energie jako hlavní zdroj pro výrobu elektrické energie.Nejdůležitější výhodou je, že vodní energie je zelená energie, což znamená, že žádné vzdušné nebo vodní znečišťující látky nejsou vyráběny, také žádné skleníkové plyny jako oxid uhličitý nejsou vyráběny, což činí tento zdroj energie šetrný k životnímu prostředí. A tak brání nebezpečí globálního oteplování. Použití internetové techniky k ovladání několika vodních elektráren má velmi významné výhody, jako snížení provozních nákladů a flexibilitu uspokojení změny poptávky po energii na straně spotřeby. Také velmi efektivně čelí velkým narušením elektrické sítě, jako je například přidání nebo odebrání velké zátěže, a poruch. Na druhou stranu, systém získávání dat poskytuje velmi užitečné informace pro typické i vědecké analýzy, jako jsou ekonomické náklady, predikce poruchy systémů, predikce poptávky, plány údržby, systémů pro podporu rozhodování a mnoho dalších výhod. Tato práce popisuje všeobecný model, který může být použit k simulaci pro sběr dat a kontrolní systémy pro vodní elektrárny v prostředí Matlab / Simulink a TrueTime Simulink knihovnu. Uvažovaná elektrárna sestává z vodní turbíny připojené k synchronnímu generátoru s budicí soustavou, generátor je připojen k veřejné elektrické síti. Simulací vodní turbíny a synchronního generátoru lze provést pomocí různých simulačních nástrojů. V této práci je upřednostňován SIMULINK / MATLAB před jinými nástroji k modelování dynamik vodní turbíny a synchronního stroje. Program s prostředím MATLAB SIMULINK využívá k řešení schematický model vodní elektrárny sestavený ze základních funkčních bloků. Tento přístup je pedagogicky lepší než komplikované kódy jiných softwarových programů. Knihovna programu Simulink obsahuje funkční bloky, které mohou být spojovány, upravovány a modelovány. K vytvoření a simulování internetových a Real Time systémů je možné použít bud‘ knihovnu simulinku Real-Time nebo TRUETIME, v práci byla použita knihovna TRUETIME.

碩士
義守大學
電機工程學系碩士班
97
In this thesis, a class of model reference time-delay networks with multiple time delays is investigated. Based on the time-domain approach and feedback control methodolody, an easily-implemented control is proposed to realize synchronization for a class of model reference time-delay networks with multiple time delays. Furthermore, the guaranteed exponential convergence rate can be correctly estimated. Finally, several numerical examples and computer simulations are provided to illustrate the feasibility and effectiveness of the obtained results.

Thesis (M. Sc.)--University of Alberta, 2009.
Title from pdf file main screen (viewed on Dec. 10, 2009). "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science in Chemical Engineering, Department of Chemical and Materials Engineering, University of Alberta." Includes bibliographical references.

This thesis describes the generic modeling of a Doubly-Fed Induction Generator (DFIG) based wind turbine. The model can also represent a wind plant with a group of similar wind turbines lumped together. The model is represented as a controlled current source which injects the current needed by the grid to supply the demanded real and reactive power. The DFIG theory is explained in detail as is the rationale for representing it by a regulated current source. The complete model is then developed in the time-domain and phasor domain by the interconnection of various sub-systems, the functions of which have been described in detail. The performance of the model is then tested for steady-state and dynamic operation. The model developed can be used for bulk power system studies and transient stability analysis of the transmission system. This thesis uses as its basis a report written for NREL [1].
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碩士
朝陽科技大學
工業工程與管理系
103
This thesis studies the optimal run time for a vendor-buyer integrated EPQ model with breakdown, (n+1) shipping plan, and the optimal production-shipment policy for a multi-item two-stage production system with delayed product differentiation. We assumed both inventory models the production process are not perfect, i.e. with defective items. All defective items produced will be reworked and there is failures in rework. Two mathematical models are developed, respectively: (1) in Part 1 of this thesis, a production system with stochastic machines breakdown, under AR (abort / resume) policy is examined. When the machine breakdowns it is under repair immediately and after repair it continues to complete the production of unfinished lot. The product distribution adopts (n+1) deliveries policy. (2) in Part 2 of this thesis, production-shipment decisions under different production schemes for a multi-item two-stage imperfect production system with delayed product differentiation are studied. The main goal focuses on determining the common cycle and delivery policy. Numerical examples with sensitivity analyses and comparisons are provided to demonstrate the practical usages and contribution of our obtained results.

This dissertation proposed a new methodology for determining the optimal operating strategies for a chilled water storage system under a Time-of-Use electricity rate structure. It is based on a new classification of operating strategies and an investigation of multiple search paths. Each operating strategy consists of a control strategy and the maximum number of chillers running during the off-peak and on-peak periods. For each month, the strategy with the lowest monthly billing cost and minimal water level higher than the setpoint is selected as the optimal operating strategy for the current month. A system model is built to simulate the tank water level at the end of each time step and the system total power during each time step. This model includes six sub-models. Specifically, the plant model is a forward model using a wire-to-water concept to simulate the plant total power. For the Thermal Energy Storage (TES) model, the tank state is described with total chilled water volume in the tank and its derivation is the tank charging or discharging flow rate. A regression model is adopted to simulate the loop supply and return temperature difference as well as the loop total flow rate demand. In the control strategy sub-model, except for three conventional control strategies and the operation without TES, a new control strategy is advanced to load the chiller optimally. The final results will be a table showing the monthly control strategy and maximal number of chillers staged on during the off-peak and on-peak periods, an approach which is easy for the operators to follow. Two project applications of this methodology are introduced in this dissertation. One is an existing TES system with state-of-the-art control and metering systems. The monthly optimal operating strategies are generated, which will achieve significant savings. The comparisons among different control strategies are also provided. The other application consists of multiple plants with little data. The purpose of the study is to evaluate the economic feasibility of designing a new chilled water storage tank and sharing it among four plants. This problem can be solved with a simplified system model, and an optimal tank size is recommended.