The essential characteristics of large systems is their high dimensionality due to which conventional control techniques fail to give reasonable solutions with reasonable computational efforts. A number of large systems encountered in practice are composed of subsystems with similar dynamics interconnected in a symmetrical fashion. The analysis and control of a large system with these particular features must take advantage of the existing structural properties to achieve computational simplifications of the overall problem. The focus of this thesis is the feedback design and analysis of large systems possessing the property of spatial symmetry. Specifically, the problems of controller design and analysis for infinite dimensional toeplitz systems and their finite dimensional analogs, circulant systems, are studied. These spatially symmetric systems are special classes of large systems. The first part of this thesis is focused on the development of formal controller design methodologies which take advantage of the properties of the circulant matrices. The key to this development is the use of the FFT algorithm to diagonalize circulant matrices. The resulting controller design methodologies are computationally attractive and easily applicable to large systems with circulant symmetry. More specifically, the H$\sb2$ and H$\sb{\infty}$ controller synthesis problems are studied in detail and are shown to decompose into lower order independent problems. The second part of this work concentrates on proving that certain finite order toeplitz systems are asymptotically equivalent in an appropriate sense to circulant systems. This result justifies the use of circulant control design techniques for certain toeplitz systems. Moreover, the closed loop effects of controlling a toeplitz system with a controller designed for its asymptotically equivalent circulant system are analyzed. The application of the developed theoretical results to a realistic example is the focus of the last part of the thesis. The adaptive optics system used in this example is modeled by a transfer function matrix with toeplitz symmetry. The computational efficiency of the controller design methodologies developed in this thesis is illustrated by designing a series of controllers for this system.

Communication networks have experienced tremendous growth in recent years, and it has become ever more challenging to design, control and manage systems of such speed, size and complexity. The traditional performance modeling tools include analysis, discrete-event simulation and network emulation. In this dissertation, we propose a new approach for performance modeling and we call it time-driven fluid simulation. Time-driven fluid simulation is a technique based on modeling the traffic going through the network as continuous fluid flows and the network nodes as fluid servers. Time is discretized into fixed-length intervals and the system is simulated by recursively computing the system state and advance the simulation clock. When the interval length is large, each chunk of fluid processed within one interval may represent thousands of packets/cells. In addition, since the simulation is synchronized by the fixed time intervals, it is easy to parallelize the simulator. These two factors enable us to tremendously speed up the simulation. For single class fluid with probability routing, we prove that the error introduced by discretizing a fluid model is within a deterministic bound proportional to the discretization interval length and is not related to the network size. For multi-class traffic passing through FIFO servers with class-based routing, we prove that the worst case discretization error for any fluid flow may grow linearly with the number of hops the flow passes but unaffected by the overall network size and the discretization error of other classes. We further show via simulation that certain performance measures are in fact quite robust with respect to the discretization interval length and the path length of the flow (in number of hops), and the discretization error is much smaller than that given by the worst case bound. These results show that fluid simulation can be a useful performance modeling tool filling the gap between discrete-event simulation and analysis. In this dissertation, we also apply another technique, rational approximation, to estimate the cell loss probabilities for an ATM multiplexer fed by a self-similar process. This is another method that compensates the analysis and simulation techniques.

The main focus of this dissertation is the dynamic allocation of discrete-resources in the context of Discrete Event Systems (DES). For this purpose, we develop two algorithms that can be used to address such problems. The first one, is descent, in other words at every iteration proceeds to an allocation with a lower cost, and it is suitable for problems with separable convex structure. Furthermore, at every iteration it visits feasible allocations which makes it appropriate for use on-line. The second one, is incremental, that is, it starts with zero resources, and at every step it allocates an additional resource. Both algorithms are proven to converge in deterministic as well as stochastic environments. Furthermore, because they are driven by ordinal comparisons they are robust with respect to estimation noise and converge fast. To complement the implementation of the derived optimization algorithms we develop two techniques for predicting the system performance under several parameters while observing a single sample path under a single parameter. The first technique, Concurrent Estimation, can be directly applied to general DES. On the other hand, for the second one, referred to as Finite Perturbation Analysis (FPA), we demonstrate a general procedure for deriving this algorithm from the system dynamics. Moreover, both procedures can be used for systems with general event lifetime distributions. The dissertation ends with three applications of variations of the developed resource allocation methodologies on three practical problems. First, the incremental algorithm is used on a kanban-based manufacturing system to find the kanban allocation that optimizes a given objective function (e.g., throughput, mean delay). Next, a variation of the descent algorithm is used to resolve the channel allocation problem in cellular telephone networks as to minimize the number of lost calls. Finally, a combination of the FPA and kanban approaches are used to solve the ground holding problem in air traffic control to minimize the congestion over busy airports.

Data communication networks have been experiencing tremendous growth in size, complexity, and heterogeneity over the last decade. This trend poses a significant challenge to the modeling, simulation, and analysis of the networks. In this dissertation, we take the fluid model as the way to attack the issue and apply it to network simulation, and to the analysis of queues. Traditional discrete-event packet-based approaches to simulating computer networks become computationally infeasible as the number of network nodes or their complexity increases. An alternative approach, in which packet-based traffic sources are replaced by fluid sources, has been proposed to address this challenge. We quantitatively characterize the amount of computational effort needed by a simulation scheme using the notion of a simulation's event rate, and derive expressions for the event rate of a packet and fluid flow at both the input and output sides of a queue. We show that the fluid-based simulation of First In First Out (FIFO) networks requires less computational effort when the network is small. However, the so-called “ripple effect” can result in fluid-based simulations becoming more expensive than their packet-based counterparts. Replacing FIFO with weighted fair queuing reduces the ripple effect, however the service rate re-distribution process incurs extra event rate. We then propose time-stepped hybrid simulation (TSHS) to deal with the scalability issue faced by traditional packet-based discrete event simulation method and fluid-based simulation methods. TSHS is a framework that offers the user the flexibility to choose the simulation time scale so as to trade off the computational cost of the simulation with its fidelity. Simulation speedup is achieved by evaluating the system at coarser time-scales. The potential loss of simulation accuracy when fine time-scale behavior is evaluated at a coarser time-scale is studied both analytically and experimentally. In addition, we compare an event-driven TSHS simulator to the time-driven version, and find out that the time-driven TSHS simulator out-performs event-driven simulator due to TSHS simulation model's time-driven nature and the simplicity of time-driven scheme. In this dissertation, we also apply the fluid model, together with the theory of stochastic differential equations, to the queueing analysis. We formulate and solve a number of general questions in this area using sample path methods as an important part of the process. Relying on the theory of stochastic differential equations, this approach brings to bear a heretofore ignored but quite effective problem solving methodology.

The study was conducted to investigate the design, and implementation of an interprofessional continuing education (IPE) course in biomedical ethics to healthcare providers; and to evaluate this course. The impact of the course on teamwork and perception among participants was also examined. The course was designed using a problem-based learning (PBL) approach using the We Learn framework (Macdonald, Stodel, Thompson, & Casimiro, 2009). The study was conducted in the Ministry of Health in Oman. The participants of the study included the instructional designer (who was also the researcher), the course instructor, five group instructors, and 28 learners. The learners were different healthcare professionals who work in the four tertiary hospitals in the capital city. The study employed design and development research (Richey & Klein, 2007) and focused on examining the process of product development and evaluation. A case study method was applied for data collection. Data were collected from all of the participants using surveys, interviews, and logs. The study findings indicated there was a decrease in learners' perceptions that may be due to unrealistic entry level. However, they expressed that working in IPE was enjoyable. They had consensus that PBL was appropriate and promoted interactions between learners. Overall, the course was implemented as designed. The course is to be revised and include cases with local context. / A Dissertation submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester 2015. / April 27, 2015. / Design and Development, Health Professional Education, Instructional Design, Interdisciplinary Education, Interprofessional Education, Problem Based Learning / Includes bibliographical references. / James Klein, Professor Directing Dissertation; James Whyte, IV, University Representative; Vanessa Dennen, Committee Member; Fengfeng Ke, Committee Member.

Experiments indicate the applicability and potential of adaptive systems for chemical process control. Stability results based on ideal conditions show that these systems asymptotically converge to the desired behavior. However, unpredictable behavior can result due to the nonlinear relationships between model uncertainty, operating conditions and the tuneable parameters of adaptive control system. The purpose of this thesis is to study the effects of model uncertainty on adaptive control systems. Global input-output and local asymptotic stability analyses are used to quantify the range of operating conditions and tuneable parameters which allow good performance for a given degree of model uncertainty. The results are used to develop better adaptive control and optimization algorithms. A nonlinear adaptive control scheme is developed which combines nonlinear model-based compensation with adaptive estimation techniques, and its stability is analyzed for a specific class of nonlinear systems. Conic sector bounds on the mismatch between the compensator and process nonlinearities are developed which guarantee global input-output stability of the feedback system. A design method is proposed which uses approximate steady-state process models. Distillation column and CSTR simulation studies reveal improved performance which results from the nonlinear compensation scheme. The concept of coupling nonlinear compensation with adaptive estimation is used to develop a novel approach to optimization based on the construction of a locally valid static relationship from approximate models and local geometric characteristics. Simulations and experiments illustrate the performance of the adaptive extremum controller on a continuous fermentor. The results from global input-output stability analyses are limited because boundedness properties can be preserved despite poor performance; however, local asymptotic analysis based on linearization and bifurcation theory provides a means of studying the effects of model uncertainty on the performance of adaptive controllers. Two simple examples are analyzed and it is shown that adaptive controllers can perform poorly in the presence of model uncertainty for certain operating conditions and tuneable parameters. Local stability boundaries are computed from the analysis; various routes to global instability and chaos are identified; and design guidelines and algorithmic modifications for a simple class of model-reference adaptive controllers are developed.

Large chemical plants are usually designed by combining several individually well controlled process units into a whole. This practice produces satisfactory, controlled response if the dynamic interactions are "weak". However, high material and energy costs and increased market competition have driven chemical plants towards a higher degree of energy integration and material recycle. These "modern" plants become difficult to operate and control because strong interconnections generally degrade the performance of the individual units, and in some cases the total response for the plant may be unstable. Our study focuses on modifying the plant design and improving control configurations to regain stability and to obtain the original output trajectories of the units as closely as possible. Via a sequential procedure, we represent the plant by a hierarchical set of self-similar modules, in which the top level represents the entire plant. The analysis of the synthesis procedures depends on a proposed measure of interaction, $\phi$, whose minimization produces the required guidelines for stable design and control.

<div>Design is complex and an important way to deal with the difficulties of design is to meet designer needs within the product development process. Many design methodologies are inapplicable and inappropriate in design practice because they were developed to be context-free universal processes. This thesis argues that design involves social and technical context. The social context influences the design process through social factors like negotiation. Negotiation will determine the outcome of major design decisions. Therefor the design process should guide designers in addressing social factors. The technical context influences design through how the design requirements are linked with the non-static environment in which design takes place. Therefor the design process should guide the designer in addressing the technical context as each tool or design methodology will determine the very character of the solution space. This thesis will identify the social and technical designer needs. This Thesis then builds on the core concepts of Collective System Design and Decision Drive Design to create a guideline for conceptual product design. This thesis then applies the guideline to develop a product to show that meeting designer needs will improve conceptual product development. </div><div><br></div>

As distance learning becomes increasingly prevalent in higher education in the 21st century, students and educators alike face new challenges to achieving key learning objectives, such as the attainment of critical thinking skills. Asynchronous threaded discussions in online classrooms provide a context where learners can develop and demonstrate their critical thinking skills. However, in an asynchronous threaded discussion, the learner is burdened with the need to retain the context and progression of multiple and concurrent ideas being developed and refined across a series of posts organized in different threads. Extraneous cognitive load caused by poorly organized discussions creates a potential barrier to critical thinking. It is anticipated that learners could benefit from a requirement to include descriptive titles on all posts to create a discussion forum index which would act as an advance organizer to help them form a mental representation of the overall structure of the discussion prior to reading each post. The purpose of this study is to determine the effect that requiring students to customize posts with descriptive titles, as a form of advance organizer, has on cognitive load and level of critical thinking exhibited in students' posts in asynchronous threaded discussions. This study is grounded in dialogic theory, cognitive load theory, and assimilation theory, which together provide a basis for the following research questions: What effect do descriptive post titles have on critical thinking in a debate on an asynchronous threaded discussion board? What effect do descriptive post titles have on cognitive load in a debate on an asynchronous threaded discussion board? This study used a mixed methods design consisting of both a quasi-experiment yielding quantitative data, and also a qualitative review of transcript data using a grounded theory approach. The quasi-experimental portion of the design consisted of collecting discussion board posts from a control group and an experimental group. Response patterns in the collected discussion board data were sequentially analyzed to identify the effects of descriptive post titles on response patterns that might demonstrate higher levels of critical thinking. A significantly higher number of challenges to arguments and explanations to arguments was found in the experimental group. A content analysis of the posts was conducted and a significantly higher number of indicators of critical thinking were found in the experimental group, while a significantly higher number of indicators of a lack of critical thinking were found in the control group. A composite cognitive load score was computed for each participant, based on measures from their average surface electromyography, average galvanic skin response, and average heat flux. Self-rated mental effort scores were also collected from each participant. The mean composite cognitive load scores were significantly higher in the control group than the experimental group, indicating that the physiological measures were effective in predicting cognitive load levels, whereas the self-rated mental effort scores were not effective in distinguishing cognitive load. A composite critical thinking score was developed for each individual and a correlation was confirmed between individual level of cognitive load and individual attainment of critical thinking in the discussion. Recommendations are made for how to incorporate these findings into learning management system software, as well as best practices for designing and facilitating discussion boards. The benefit to society of this study is that increasing the critical thinking skills of college students will better prepare graduates to meet the complex demands of the modern workforce and to be responsible members of society. / A Dissertation submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the Doctor of Philosophy. / Spring Semester, 2015. / April 10, 2015. / advance organizers, biometrics, cognitive load, critical thinking, distance learning, instructional design / Includes bibliographical references. / Allan C. Jeong, Professor Directing Dissertation; John K. Mayo, University Representative; Vanessa P. Dennen, Committee Member; Valerie J. Shute, Committee Member.

Erroneous decisions made by pilots during encounters with adverse weather is often cited as a cause of General Aviation accidents. Pilot experience, which can be measured in several ways, is believed to play a role in the outcome of such encounters. However, it is unclear whether any of the elements of experience alone or in combinations affect the likelihood of General Aviation accidents during actual encounters with adverse weather, or how they do so. One barrier to conclusively determining such effects is the danger in extrapolating simulation results to the real world; nearly all work done to date has used simulators to identify accident risk. Therefore, the extent to which such results can be applied to actual flying is not clear.<div><br></div><div>In this work, two conceptual models for analyzing experience and its role inencounters with adverse weather during the cruise phase of General Aviation Part 91 fixed wing operations are presented. A novel method for evaluating accident risk, specifically the likelihood that an incident turns into an accident is also presented and then used to evaluate the experience profile of 595 pilots, detailed in actual accident and incident reports from the NTSB and ASRS databases. The effect of various elements of experience, alone and in combinations, on that risk is evaluated using regression modeling. The level of significance for each experience variable is first established, and then a series of discrete models is developed to progressively evaluate accident risk along a hypothetical experience continuum. This approach obviates commonly encountered challenges with research in the area and provides results that are ecologically valid.<br></div><div><br></div><div>The focus of this research work was on the role of cognitive aspects of experience in the outcome of flights during the cruise phase of General Aviation Part 91 fixed wing flights between January 1, 2005 and December 31, 2015. Only flights which encountered adverse weather during the cruise phase and for which experience and/or errors in decision making were determined to be a cause or factor in the outcome were included in the study. All flights during the period that involved takeoff and landing, equipment failure or student pilots were not considered for the study. The emphasis of the research was on the effect of experience on cognitive aspects of pilot performance during adverse weather encounters, rather than “stick and rudder” skills.<br></div><div><br></div><div>It was found that variables related to the breadth or variety of pilots’ experience are more predictive of the likelihood of adverse weather encounters turning into accidents compared to those related to the duration or length of experience. While several commonly used measures of experience provide some level of insulation against accidents, the relationship between elements that define the length or duration of experience and outcomes is not linear. Furthermore, this relationship is mediated by variables that define the breadth of experience, especially at their lower levels. These findings may be leveraged to design specifically targeted regulatory or training policies and interventions to expedite the transition from novice to expert pilots in General Aviation weather-related decision making.<br></div>