Browsing by Subject "Control"
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Item A novel feedback design method for mimo QFT with application to the X-29 flight control problem(2009-05-15) Lan, Chen-YangQuantitative Feedback Theory (QFT) method employs a two degree of freedom control configuration that includes a feedback controller and a prefilter in the feedforward path. When applied to multi-input multi-output (MIMO) systems, the QFT method calls for a special decomposition of the MIMO system. Specifically, the MIMO system is decomposed into multiple multi-input single-output (MISO) equivalent systems, and is followed by the single-input single-output (SISO) QFT design of each equivalent system. Depending on pole-zero structure of the equivalent SISO plants so obtained, the QFT design may become unnecessarily difficult/conservative or even infeasible. This situation is especially true for linear time invariant (LTI) systems with non-minimum phase (NMP) zero(s) and unstable pole(s). This unnecessary design difficulty and the challenge of dealing with MIMO systems that have unstable poles and NMP transmission zeros in undesirable locations, when MIMO QFT is considered, is investigated and addressed in this research. A new MIMO QFT design methodology was developed using the generalized formulation. The key idea of the generalized formulation is to utilize appropriate modifications at the plant input and/or the output to obtain a better conditioned plant that in turn can be used to execute a standard MIMO QFT design. The formulation is based on a more general control structure, where input and output transfer function matrices (TFM) are included to provide additional degrees of freedom in the typical decentralised MIMO QFT feedback structure, which facilitates the exploitation of directions in MIMO QFT designs. The formulation captures existing design approaches for a fully populated MIMO QFT controller design and provides for a directional design logic involving the plant and controller alignment and the directional properties of their multivariable poles and zeros. As a case in point Horowitz?s Singular-G design methodology is placed in the context of this generalized formulation, and the Singular-G design for the X-29 is analysed and redesigned using both non-sequential and sequential MIMO QFT demonstrating its utility. The results highlight a fundamental trade-off between multivariable controller directions for stability and performance in classically formulated MIMO QFT design methodologies, which elucidate the properties of Singular-G designed controllers for the X-29 and validate the developed new MIMO QFT design method.Item A Real Time Expert Control System for Helicopter Autorotation(2013-04-22) Sunberg, Zachary NolanAutorotation maneuvers are required to perform a safe landing of a helicopter in cases of engine loss in a single engine vehicle and transmission or tail rotor malfunction. The rise of autonomous helicopter technology, and the pilot skill required to manually perform an autorotation, motivate the need for new autonomous autorotation control laws. Previous approaches to automatic control for this maneuver have relied on control law optimization based on a high-fidelity model of the helicopter, or have attempted to match recorded trajectories flown by an expert human pilot. In this paper, a new expert control system is proposed. The term ?expert control system? is used because the system is intended to mimic the actions that a human pilot might take, does not require any iterative learning, model prediction, or optimization at runtime, and is based on an inference system that involves fuzzy logic, PID, and other conventional control techniques. The multi-stage control law drives the helicopter to a near-optimal steady-state descent and uses an estimate of the time to impact to safely flare and land the helicopter in the vast majority of flight conditions. The control law is validated using a full 6-degree-of-freedom simulation of both a full-size attack helicopter and a small hobby-class helicopter. The pro- posed control design is highly flexible and may be used to perform fully autonomous autorotation or to provide guidance to pilots during manual autorotation maneuvers.Item Adaptive control for Mars atmospheric flight(2009-05-15) Restrepo, Carolina IsabelThe new vision for space exploration will focus on sending humans to the moon and eventually to Mars. This endeavor presents new challenges that are critically di?erent from the past experience with robotic missions to Mars. For example, the strict landing accuracy requirements for a manned space vehicle make it necessary to ?y a controlled entry trajectory rather than a more robust ballistic entry trajectory used for some robotic missions. The large variations in Mars atmospheric properties make a controlled entry and a safe precision landing for manned missions a di?cult engineering problem. Model reference adaptive control is a candidate solution for the Mars entry control problem. This type of controller has an adaptation mechanism that reduces tracking errors in the presence of uncertain parameters such as atmospheric density or vehicle properties. This thesis develops two di?erent adaptive control systems for the Mars ellipsled, a vehicle which is much larger than those that carried robotic payloads to Mars in the past. A sample mission will have multiple ellipsleds arriving at Mars carrying an assortment of payloads. It is of critical importance that the vehicles land in close proximity to each other to best assure that the crew has manageable access to their payloads. The scope of this research encompasses the atmospheric ?ight of the ellipsled, starting at the entry interface point through the ?nal parachute deployment. Tracking performance of an adaptive controller for prescribed entry trajectories in the pres?ence of atmospheric and vehicle model uncertainties is shown here. Both adaptive controllers studied in this thesis demonstrate successful adaptation to uncertainties in the Martian atmosphere as well as errors in the vehicle properties. Based on these results, adaptive control is a potential option for controlling Mars entry vehicles.Item Analysis and order reduction of an autonomous lunar lander navigation system(2009-08) Newman, Clark Patrick; Bishop, Robert H., 1957-; Akella, Maruthi R.A navigation system for precision lunar descent and landing is presented and analyzed. The navigation algorithm is based upon the extended Kalman Filter and employs measurements from an inertial measurement unit to propagate the vehicle position, velocity, and attitude forward in time. External measurements from an altimeter, star camera, terrain camera, and velocimeter are utilized in state estimate updates. The navigation algorithm also attempts to estimate the values of uncertain parameters associated with the sensors. The navigation algorithm also estimates the map-tie angle of the landing site which is a measure of the misalignment of the actual landing site location on the surface of the Moon versus the estimated position of the landing site. The navigation algorithm is subject to a sensitivity analysis which investigates the contribution of each error source to the total estimation performance of the navigation system. Per the results of the sensitivity analysis, it is found that certain error sources need not be actively estimated to achieve similar estimation performance at a reduced computational burden. A new, reduced-order system is presented and tested through covariance analysis and a monte carlo analysis. The new system is shown to have comparable estimation performance at a fraction of the computer run-time, making it more suitable for a real-time implementation.Item Analysis of the power grid: structure and secure operations(2015-08) Deka, Deepjyoti; Vishwanath, Sriram; Baldick, Ross; Kwasinski, Alexis; Meyers, Lauren A.; Moorty, SainathPower Grids form one of the vital backbone-networks of our society providing electricity for daily socio-economic activities. Given its importance, there is a greater need to understand the structure and control of the power grid for fair power market computations and efficient delivery of electricity. This work studies two problems associated with different aspects of today's power grid network and combines techniques from network science, control theory and optimization to analyze them. The first problem relates to understanding the common structural features observed in several power grids across the world and developing a trackable modeling framework that incorporates these features. Such a framework can lead to insights on structural vulnerability of the grid and help design realistic test cases to study effects of structural and operational reinforcements as the grid evolves with time. We develop a generative model based on spatial point process theory that provably produces the distinct exponential degree distribution observed in several power grids. Further, critical graph parameters like diameter, eigen-spread, betweenness centralities and clustering coefficients are used to compare the performance of our framework in modeling the power grids in Western USA and under ERCOT in Texas. The second problem discussed here involves a detailed study of malicious data attacks on state estimation in the power grid. Such data attacks pose a serious threat to efforts related to implementing distributed control for efficient operations in the grid. We develop a graph-theoretic framework to analyze the design of optimal data attacks and study cost-optimal techniques to build resilience against them. The study involves attacks by a practical adversary capable of modifying meter readings as well as of jamming the flow of information from meters to the grid controller. We prove that the design of optimal `hidden' and `detectable' attacks can be formulated as constrained graph-cut problems that depend on the relative costs of adversarial techniques, and present algorithms for attack construction. Further, we design a new `topology' attack regime where an adversary changes beaker statuses of grid lines to affect state estimation in systems where all meter measurements are encrypted and hence secure from manipulation. We discuss bounds on the security requirements imposed by the developed attack models and design algorithms for determining the optimal protection strategy. This helps present an accurate characterization of grid vulnerability to general data attacks and eavesdroppers and motivates efforts to expand the presence of new secure meters to foil cyber attacks in the grid.Item An attitude determination and control system for small satellites(2015-05) Tam, Margaret Hoi Ting; Fowler, Wallace T.; Lightsey, E. GlennA flexible, robust attitude determination and control (ADC) system is presented for small satellite platforms. Using commercial-off-the-shelf sensors, reaction wheels, and magnetorquers which fit within the 3U CubeSat form factor, the system delivers arc-minute pointing precision. The ADC system includes a multiplicative extended Kalman filter for attitude determination and a slew rate controller that acquires a view of the Sun for navigation purposes. A pointing system is developed that includes a choice of two pointing controllers -- a proportional derivative controller and a nonlinear sliding mode controller. This system can reorient the spacecraft to satisfy a variety of mission objectives, but it does not enforce attitude constraints. A constrained attitude guidance system that can enforce an arbitrary set of attitude constraints is then proposed as an improvement upon the unconstrained pointing system. The momentum stored by the reaction wheels is managed using magnetorquers to prevent wheel saturation. The system was thoroughly tested in realistic software- and hardware-in-the-loop simulations that included environmental disturbances, parameter uncertainty, actuator dynamics, and sensor bias and noise.Item Azharite Clerics in Egypt : protection of their professional role in a changing religious and political environment, 1805-1968(2015-05) Cumming, Willis Winfield; Di-Capua, Yoav, 1970-; Moin, Azfar AThis study seeks to investigate the relationship of the religious seminary, Azhar, in Egypt between the years of Muhammad Ali's reign (1805-1849), and the 1960s under Gamal Abdel Nasser (1918-1970). It pays special attention to the relationship that developed as a result of the "Development of Azhar Law" that Nasser promulgated in 1961. While the change in politics and popular religious culture during the late nineteenth and early twentieth century initially created difficulties for the institution’s religious scholars in preserving their professional role in Egyptian society, Azhar gained a new political importance as a center for producing works of apology in favor of Nasser's post-colonial regime. This new relationship proved auspicious not only for the state who could rely on Azhar's support against written attacks against it by Islamists, but also for the institution itself which gained the security of state financial support and a vested interest of the state in keeping the seminary graduates employed and active in social and political life. This transformation, although giving the institution a new political relevance, compromised its independence from state control to the point where it incorporated pro-state propaganda into its religious message. Consideration of these historical phenomena lead us to wonder about resulting legacy of Azhar's religious message and the implications it has for popular religion and politics in Egypt.Item Closed-loop control of shock location to prevent hypersonic inlet unstart(2014-08) Ashley, Jonathan Michael; Akella, Maruthi Ram, 1972-Hypersonic inlet unstart remains a major technical obstacle in the successful implementation of hypersonic air-breathing propulsion systems such as ramjets and scramjets. Unstart occurs when combustor-induced pressure fluctuations lead to rapid expulsion of the shock system from the isolator, and is associated with loss of thrust. The research presented here attempts to mitigate this behavior through the design and implementation of a closed-loop control scheme that regulates shock location within a Mach 1.8 wind tunnel isolator test section. To localize the position of the shock within the isolator, a set of high frequency Kulite pressure transducers are used to measure the static pressure at various points along the wind tunnel test section. A novel Kalman filter based approach is utilized, which fuses the estimates from two distinct shock localization algorithms running at 250 Hz to determine the location of the shock in real time. The primary shock localization algorithm is a geometrical shock detection scheme that can estimate the position of the shock system even when it is located between pressure transducers. The second algorithm utilizes a sum-of-pressures technique that can be calibrated by the geometrical algorithm in real time. The closed-loop controller generates commands every 100 ms to actuate a motorized flap downstream of the test section in an effort to regulate the shock to the desired location. The closed-loop control implementation utilized a simple logic-based controller as well as a Proportional-Integral (PI) and a Proportional-Derivative (PD) Controller. In addition to the implementation of control algorithms, the importance of various design criteria necessary to achieve satisfactory control performance is explored including parameters such as pressure transducer spacing, shock localization speed, flap-motor actuation speed and actuator resolution. Experimental results are presented for various test scenarios such as regulation of the shock location in the presence of stagnation pressure disturbances as well as tracking of time-varying step inputs. Performance and robustness properties of the tested control implementations are discussed. Further areas of improvement for the closed-loop control system in both hardware and software are discussed, and the need for reduced-order dynamics-based controllers is presented.Item A compliant control law for industrial, dual-arm manipulators(2013-05) Zelenak, Andrew J; Landsberger, Sheldon; Pryor, Mitchell WayneMany of the first robots ever built, decades even before the first industrial robots, were humanoids. It seems like researchers have always sought to imitate the human form with their robots, and with good reason. Humans are incredibly flexible; they can perform a huge variety of tasks, from locomotion over rough terrain, to delicate assembly, to heavy lifting. A human’s second arm allows him to lift twice as much weight. His workspace is approximately doubled, and he can perform a broader variety of tasks as items are passed back and forth between hands. We sought to impart some of that same functionality to a strong, rigid, dual-arm robot. Specifically, we developed a control law that allows two robot arms to lift and manipulate an object in cooperation. As opposed to the prior art, our control law is tailored for industrial robots. These robots do not usually allow torque control and their control frequency is generally 60 Hz. Through the use of fuzzy logic, the control law is quite robust at 60 Hz control rates. Its simple structure reduces the computational cost of the algorithm by approximately 75% over Jacobian-based methods. Stability is proven and the controller parameters can be adjusted to handle perturbances of arbitrary magnitude. Since the robots behave as an admittance, torque control is not required. Several experiments were conducted to benchmark and validate the performance of this control law. The controller is able to maintain a clamp force within ± 4N despite a wide variation in trajectory and control frequency. This fine level of force control makes the controller suitable for delicate tasks. The conclusion suggests several extensions that would make this control law more useful. For example, adaptive control would improve the performance. A position feedback controller should be cascaded so that the robot arms’ tracking accuracy is improved. Many tasks (such as co-robotics) require external compliance, and we show how external compliance could easily be incorporated.Item Control and Optimization of Vapor Compression Cycles Using Recursive Least Squares Estimation(2012-10-19) Rani, AvinashVapor compression cycles are the primary method by which refrigeration and air-conditioning systems operate, and thus constitute a significant portion of commercial and residential building energy consumption. This thesis presents a data-driven approach to find the optimal operating conditions of a multi-evaporator system in order to minimize the energy consumption while meeting operational requirements such as constant cooling or constant evaporator outlet temperature. The experimental system used for controller evaluation is a custom built small-scale water chiller with three evaporators; each evaporator services a separate body of water, referred to as a cooling zone. The three evaporators are connected to a single condenser and variable speed compressor, and feature variable water flow and electronic expansion valves. The control problem lies in development of a control architecture that will minimize the energy consumed by the system without prior information about the system in the form of performance maps, or complex mathematical models. The control architecture explored in this thesis relies on the data collected by sensors alone to formulate a function for the power consumption of the system in terms of controlled variables, namely, condenser and evaporator pressures, using recursive least squares estimation. This cost function is then minimized to attain optimal set points for the pressures which are fed to local controllers.Item Control and waypoint navigation of an autonomous ground vehicle(Texas A&M University, 2006-08-16) Massey, James PatrickThis thesis describes the initial development of the Texas A&M Autonomous Ground Vehicle test platform and waypoint following software, including the associated controller design. The original goal of the team responsible for the development of the vehicle was to enter the DARPA Grand Challenge in October 2005. A 2004 Ford F150 4x4 pickup was chosen as the vehicle platform and was modified with a 6?? suspension lift and 35?? tires, as well as a commercial drive-by-wire system. The waypoint following software, the design of which is described in this thesis, is written in C and successfully drives the vehicle on a course defined by GPS waypoints at speeds up to 50 mph. It uses various heuristics to determine desired speeds and headings and uses control feedback to guide the vehicle towards these desired states. A vehicle dynamics simulator was also developed for software testing. Ultimately, this software will accept commands from advanced obstacle avoidance software so that the vehicle can navigate in true off-road terrain.Item Control of solitons in mems actuator arrays(Texas Tech University, 2006-05) Palamakumbura, Rathnamali; Dayawansa, Wijesuriya P.; Martin, Clyde F.; Inaba, H.; Berg, Jordan M.; Barnard, Roger W.Signal transmission in large arrays MEMS and NEMS devices will be a major issue due to the sheer complexity, and it is likely that solutions to ensuing problems will have much in common with complex networks in the biological world. Motivated by this we specifically address the problem of how one may generate a compendium of stable travelling pulse patterns in a linear array of microactuators by controlling their own inherent dynamics appropriately. The approach we take is two fold. First we pick a known system that produces the desired patterns and derive controls that ensure smooth and quick transition from one pattern to another. Then we expect to embed these controlled dynamics into the linear array of actuators using standard available model based control strategies. The problem of transition from one pattern to another in a smooth and quick fashion has received only scant attention. We focus on a class of systems that possess special type of solutions known as solitons. All of the hitherto known soliton producing equations are completely integrable and can be expressed in a special form known as the Lax form. In the Lax formulation the problem of complete integrability is transformed into an analyticity problem on a Riemann surface referred to as the spectral curve. This allows one to relate the properties of the solution to the properties of the spectral curve. It can be shown that given a solution there exists an associated unique spectral curve and that given a spectral curve there exists a corresponding class of solutions that evolve on a unique g dimensional torus of the state space where g is the genus of the spectral curve. We classify solutions by their respective spectral curves and reduce the problem of smooth and quick transition from one class to another to that of a setpoint control problem on the space of spectral curves. It is the first time such results have been shown. The results are general and are applicable in a very wide sense. Namely, to any Liouville integrable system.Item Control, learning, and innovation : a syncretic approach(2010-05) Romo de Vivar y Sandoval, Carmen Alejandra; Browning, Larry D.This research focuses on understanding the processes involved in successful innovation---a topic that has appeared in a large body of research, but no conclusive trend has emerged about it. For this reason, I chose a different lens in order to gain a more panoramic view of the events leading up to an innovation. In particular, this research utilized a methodology and ontology that set it apart from previous work. In previous research control/exploitation and learning/exploration are either presented as two categorically separate concepts or as continuum that runs between them. This research supports the idea that innovation operates on a continuum but does not support the idea that it only occurs when the pendulum settles toward the learning/exploration side. Instead, the data shows that innovation could indeed occur at any point along the learning/exploration side of the continuum and even at the central point where learning/exploration and control/exploitation weigh evenly. To conceptualize this middle point, I term this a "syncretism" of two normally opposing forces to account for a significant portion of the interview data.Item A critical evaluation of modern low-thrust, feedback-driven spacecraft control laws(2012-12) Hatten, Noble Ariel; Ocampo, Cesar; Akella, MaruthiLow-thrust spacecraft trajectory optimization is often a difficult and time-consuming process. One alternative is to instead use a closed-loop, feedback-driven control law, which calculates the control using knowledge of only the current state and target state, and does not require the solution of a nonlinear optimization problem or system of nonlinear equations. Though generally suboptimal, such control laws are attractive because of the ease and speed with which they may be implemented and used to calculate feasible low-thrust maneuvers. This thesis presents the theoretical foundations for seven modern low-thrust control laws based on control law "blending" and Lyapunov control theory for a particle spacecraft operating in an inverse-square gravitational field. The control laws are evaluated critically to determine those that present the best combinations of thoroughness of method and minimization of user input required. The three control laws judged to exhibit the most favorable characteristics are then compared quantitatively through three numerical simulations. The simulations demonstrate the effectiveness of feedback-driven control laws, but also reveal several situations in which the control laws may perform poorly or break down altogether due to either theoretical shortcomings or numerical difficulties. The causes and effects of these issues are explained, and methods of handling them are proposed, implemented, and evaluated. Various opportunities for further work in the area are also described.Item Data-driven modeling and optimization of sequential batch-continuous process(2016-05) Park, Jungup; Edgar, Thomas F.; Baldea, Michael; Djurdjanovic, Dragan; Rochelle, Gary T; Truskett, Thomas MDriven by the need to lower capital expenditures and operating costs, as well as by competitive pressure to increase product quality and consistency, modern chemical processes have become increasingly complex. These trends are manifest, on the one hand, in complex equipment configurations and, on the other hand, in a broad array of sensors (and control systems), which generate large quantities of operating data. Of particular interest is the combination of two traditional routes of chemical processing: batch and continuous. Batch to continuous processes (B2C), which constitute the topic of this dissertation, comprise of a batch section, which is responsible for preparing the materials that are then processed in the continuous section. In addition to merging the modeling, control and optimization approaches related to the batch and continuous operating paradigms --which are radically different in many aspects-- challenges related to analyzing the operation of such processes arise from the multi-phase flow. In particular, we will be considering the case where a particulate solid is suspended in a liquid ``carrier'', in the batch stage, and the two-phase mixture is conveyed through the continuous stage. Our explicit goal is to provide a complete operating solution for such processes, starting with the development of meaningful and computationally efficient mathematical models, continuing with a control and fault detection solution, and finally, a production scheduling concept. Owing to process complexity, we reject out of hand the use of first-principles models, which are inevitably high dimensional and computationally expensive, and focus on data-driven approaches instead. Raw data obtained from chemical industry are subject to noise, equipment malfunction and communication failures and, as such, data recorded in process historian databases may contain outliers and measurement noise. Without proper pretreatment, the accuracy and performance of a model derived from such data may be inadequate. In the next chapter of this dissertation, we address this issue, and evaluate several data outlier removal techniques and filtering methods using actual production data from an industrial B2C system. We also address a specific challenge of B2C systems, that is, synchronizing the timing of the batch data need with the data collected from the continuous section of the process. Variable-wise unfolded data (a typical approach for batch processes) exhibit measurement gaps between the batches; however, this type of behavior cannot be found in the subsequent continuous section. These data gaps have an impact on data analysis and, in order to address this issue, we provide a method for filling in the missing values. The batch characteristic values are assigned in the gaps to match the data length with the continuous process, a procedure that preserves meaningful process correlations. Data-driven modeling techniques such as principal component analysis (PCA) and partial least squares (PLS) regression are well-established for modeling batch or continuous processes. In this thesis, we consider them from the perspective of the B2C systems under consideration. Specific challenges that arise during modeling of these systems are related to nonlinearity, which, in turn, is due to multiple operating modes associated with different product types/product grades. In order to deal with this, we propose partitioning the gap-filled data set into subsets using k-means clustering. Using the clustering method, a large data set that reflects multiple operating modes and the associated nonlinearity can be broken down into subsets in which the system exhibits a potentially linear behavior. Also, in order to further increase the model accuracy, the inputs to the model need to be refined. Unrelated variables may corrupt the resulting model by introducing unnecessary noise and irrelevant information. By properly eliminating any uninformative variables, the model performance can be improved along with the interpretability. We use variable selection methods to investigate the model coefficients or variable importance in projection (VIP) values to determine the variables to retain in the model. Developing a model to estimate the final product quality poses different challenges. Measuring and quantifying the final product quality online can be limited due to physical and economic constraints. Physically, there are some quantities that cannot be measured due to sensor sizes or surrounding environments. Economically, the offline ``lab'' measurements may lead to destroying the sample used for the testing. These constraints lead to multiple sampling rates. The process measurements are stored and available continuously in real-time, but the quality measurements have much lower sampling rate. In order to account for this discrepancy, the online process measurements are down-sampled to match the sampling frequency of the lab measurements, and subsequently, soft sensors are can be developed to estimated the final product quality. With the soft sensor in place, the process needs to be optimized to maximize the plant efficiency. Using the real-time optimization, the optimal sequence of manipulated inputs that minimizes the off-spec products are calculated. In addition, the optimal sequences of setpoints can be calculated by carrying out the scheduling calculation with the process model. Traditionally, the scheduling calculation is carried out without taking the process dynamics into account, which could result in off-spec products if a disturbance is introduced. Incorporating the process dynamics into the scheduling layer poses many different challenges numerically. The proposed time scale bridging model (SBM) is able to capture the input-output behavior of the process while greatly reducing the computational complexity and time.Item Design of a CubeSat guidance, navigation, and control module(2011-08) Kjellberg, Henri Christian; Lightsey, E. Glenn.; Fowler, Wallace T.A guidance, navigation, and control (GN&C) module is being designed and fabricated as part of a series of CubeSats being built by the Satellite Design Laboratory at the University of Texas. A spacecraft attitude control simulation environment called StarBox was created in order to perform trade studies and conduct performance analysis for the GN&C module. Navigation and control algorithms were tested using StarBox and then implemented onto an embedded flight computer. These algorithms were then tested in a hardware-in-the-loop simulation. In addition, the feasibility of utilizing advanced constrained attitude control algorithms was investigated by focusing on implementation in flight software. A mechanical and electrical design for the GN&C module was completed. A prototype system was set up on a bench-top for integrated testing. The analysis indicates that the system will satisfy the requirements of several CubeSat missions, including the current missions at the University of Texas known as Bevo2 and ARMADILLO.Item Detection of switching time(2008-08) Sanghvi, Palak; Martin, Dr. Clyde F.In this thesis, we talk about detecting switches and jumps in the data. Every dataset has a certain hidden pattern in it. These patterns are sometimes irregular and abnormal because of the jumps and switches in the datasets or sometimes because of outliers in the datasets. At the point of out lier, data changes it's pattern and it looks irregular. Generally people use control limiting to detect those changes or outliers, but using control limiting one can not detect the minor changes. So, we use change point analysis along with splines and Gibbs phenomenon to detect minor shifts or changes in the dataset. But, we can not use change point analysis in stead of control charting, both methods are used in complementary fashion. Control charting is useful to detect single outliers, and change point analysis detects bunch of outliers at a time. Here our dataset is a mixture of two data sets, in which one dataset is a set of outliers. We are trying to separate these two datasets using change point analysis, and trying to find the change point in between these two datasets, This change point is called the shift or jump.Item Development of Systems to Improve Cotton Module Shape(2011-10-21) Hardin, Robert GlenProperly constructed modules will prevent reduced lint value and increased ginning costs when significant rainfall occurs. Additionally, cotton producers often have difficulty finding adequate labor during harvest. These issues were addressed by developing a graphical operator feedback system, a biomass package measurement system, a powered tramper, and an autonomous module forming system. A system that provided feedback on the module shape by recording the position of the tramper and carriage was used to direct the operator to move cotton to appropriate locations. The system correctly predicted the height of 67% of data points. Use of the feedback system resulted in a 55% reduction in water collection area of the modules. The module builder operators indicated that the system was useful. The module builder feedback system is a simple, useful, and inexpensive tool that can have a rapid payback for producers. A powered tramper, with an auger to move cotton to the center of the module, was developed to replace the conventional tramper. The powered tramper operated automatically without affecting the operating speed or pressure of the tramper cylinder. During testing, the powered tramper was observed moving cotton to the center and crowned modules were produced. A biomass package measurement system was developed to record the height at multiple points on the top surface of modules. The system was found to produce repeatable measurements with an error of 5 cm. Data collected with this system did not indicate a difference in module shape when using the powered tramper; however, during these tests the powered tramper was turned off prematurely due to an improperly sized valve on the module builder. An automated module building system capable of both moving and tramping cotton was developed. This system utilized the feedback system sensors and photoelectric sensors to determine the location of cotton in the builder. A wireless display allowed the boll buggy operator to control the automatic system. The automatic system constructed modules with 64% less water collection area in an average time of 37.4 min. Cotton producers indicated that the system was easy to use and of significant value in reducing labor requirements.Item The effects of control and uncertainty on children's supernatural beliefs(2015-05) Cornelius, Chelsea Ann; Woolley, Jacqueline D.; Bigler, Rebecca; Markman, Arthur; Reeves, Lauretta; Whitson, JenniferMost people believe that the world is orderly and predictable, and one mechanism by which this belief is maintained is a sense of personal control, or the belief that one can predict and steer outcomes. Research indicates that when adults perceive a threat to their personal control, they will compensate for this threat by seeking other sources of control. However, it is unclear whether children also feel threatened by a lack of personal control or whether they seek similar sources of compensatory control as adults. The proposed studies investigated the process of compensatory control in children. A novel game primed children to feel either high personal control or low personal control in order to evaluate the extent to which children seek compensatory control via 1) the detection of visual patterns in random noise, 2) endorsement of superstitious explanations for events, and 3) explicit belief in supernatural sources of control. Children also completed a questionnaire designed to measure their intolerance of uncertainty. It was predicted that both the manipulation of control and individual differences in children’s willingness to tolerate uncertainty would affect compensatory control seeking behaviors. Results indicated that manipulation of personal control did not affect children’s pattern detection; however, the manipulation did affect children’s endorsement of karma-like explanations, such that children in the low-control condition were significantly more likely to endorse such explanations compared to children in the high-control condition. Regarding individual differences, results indicated a positive relationship between children’s intolerance of uncertainty and their explicit belief in God. These results are interpreted with regard to existing research with adults, and the implications for situational and dispositional motivations for control are discussed.Item Embedding dynamics and control considerations in operational optimization of process and energy systems(2016-05) Touretzky, Cara Rose; Baldea, Michael; Edgar, Thomas F; Truskett, Thomas M; Bonnecaze, Roger T; Novpselac, AtilaEmbedding dynamics and control considerations within operational optimization decisions can result in improved performance of processes and energy systems. These efforts are motivated by modern sustainability initiatives, in particular demand response and demand management strategies for improving the efficiency of the electric grid. In these scenarios residential, commercial, and industrial electricity consumers are provided with a financial incentive to shift their demand such that the total load on the grid can be satisfied using efficient generation technologies and renewable energy sources. The financial incentive is typically a time-dependent price structure, where rates reflect the demand level and stress on the grid. Reacting to such fast-changing energy markets requires that process and energy systems be highly flexible, which is a significant departure from traditional steady state operation under fixed market conditions. In this context, flexibility means the ability to make frequent changes to the system operation (e.g., production setpoints, constraint levels, etc.) while still maintaining stability and satisfying operating constraints at all times. This necessitates the development of advanced control and decision making strategies which are aware of system dynamics. Accounting for dynamics by incorporating detailed, first-principles models of a system into optimization-based controllers or scheduling calculations would provide ample dynamic information. However, the resulting dynamic optimization formulations would be plagued by a large problem size, numerical difficulties associated with stiff equations and multiple time scales, and the presence of integer decisions. In this dissertation, we address these challenges through hierarchical controller designs and novel scheduling (and rescheduling) formulations including low-order models of relevant system dynamics, which are identified through an appropriate model reduction or system identification procedure. Case studies involving the built environment and chemical processes are used to demonstrate the proposed methods.
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