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Articles 601 - 630 of 839

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Route Aware Predictive Congestion Control Protocol For Wireless Sensor Networks, Carl Larsen, Maciej Jan Zawodniok, Jagannathan Sarangapani Jan 2007

Route Aware Predictive Congestion Control Protocol For Wireless Sensor Networks, Carl Larsen, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Congestion in wireless sensor networks (WSN) may lead to packet losses or delayed delivery of important information rendering the WSN-based monitoring or control system useless. In this paper a routing-aware predictive congestion control (RPCC) yet decentralized scheme for WSN is presented that uses a combination of a hop by hop congestion control mechanism to maintain desired level of buffer occupancy, and a dynamic routing scheme that works in concert with the congestion control mechanism to forward the packets through less congested nodes. The proposed adaptive approach restricts the incoming traffic thus preventing buffer overflow while maintaining the rate through an …

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Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, David A. Cartes Jan 2007

Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, David A. Cartes

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents two neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control signals are calculated using local signals only, the transient and overall system stabilities can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system and the interconnection terms, thus the requirements for exact system parameters are released. Simulation studies with a three machine power system demonstrate the effectiveness of the proposed controller designs.

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Adaptive Power Control Protocol With Hardware Implementation For Wireless Sensor And Rfid Reader Networks, Kainan Cha, Jagannathan Sarangapani, David Pommerenke Jan 2007

Adaptive Power Control Protocol With Hardware Implementation For Wireless Sensor And Rfid Reader Networks, Kainan Cha, Jagannathan Sarangapani, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

The development and deployment of radio frequency identification (RFID) systems render a novel distributed sensor network which enhances visibility into manufacturing processes. In RFID systems, the detection range and read rates will suffer from interference among high-power reading devices. This problem grows severely and degrades system performance in dense RFID networks. Consequently, medium access protocols (MAC) protocols are needed for such networks to assess and provide access to the channel so that tags can be read accurately. In this paper, we investigate a suite of feasible power control schemes to ensure overall coverage area of the system while maintaining a …

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Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier Jan 2007

Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier

Electrical and Computer Engineering Faculty Research & Creative Works

A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …

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Neural Network Control Of Robot Formations Using Rise Feedback, Jagannathan Sarangapani, Travis Alan Dierks Jan 2007

Neural Network Control Of Robot Formations Using Rise Feedback, Jagannathan Sarangapani, Travis Alan Dierks

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers that are widely reported in the literature. A neural network (NN) is introduced along with robust integral of the sign of the error (RISE) feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are asymptotically stable and the NN weights are bounded as opposed …

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Online Reinforcement Learning Control Of Unknown Nonaffine Nonlinear Discrete Time Systems, Qinmin Yang, Jagannathan Sarangapani Jan 2007

Online Reinforcement Learning Control Of Unknown Nonaffine Nonlinear Discrete Time Systems, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel neural network (NN) based online reinforcement learning controller is designed for nonaffine nonlinear discrete-time systems with bounded disturbances. The nonaffine systems are represented by nonlinear auto regressive moving average with exogenous input (NARMAX) model with unknown nonlinear functions. An equivalent affine-like representation for the tracking error dynamics is developed first from the original nonaffine system. Subsequently, a reinforcement learning-based neural network (NN) controller is proposed for the affine-like nonlinear error dynamic system. The control scheme consists of two NNs. One NN is designated as the critic, which approximates a predefined long-term cost function, whereas an …

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Reinforcement Learning Based Output-Feedback Controller For Complex Nonlinear Discrete-Time Systems, Peter Shih, Jagannathan Sarangapani Jan 2007

Reinforcement Learning Based Output-Feedback Controller For Complex Nonlinear Discrete-Time Systems, Peter Shih, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex feedback nonlinear discrete-time systems in the presence of bounded and unknown disturbances. This nonlinear discrete-time system consists of a second order system in nonstrict form and an affine nonlinear discrete-time system tightly coupled together. Two adaptive critic NN controllers are designed - primary one for the nonstrict system and the secondary one for the affine system. A Lyapunov function shows the uniformly ultimate boundedness (UUB) of the closed-loop tracking error, weight estimates …

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Near Optimal Neural Network-Based Output Feedback Control Of Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani Jan 2007

Near Optimal Neural Network-Based Output Feedback Control Of Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel online reinforcement learning neural network (NN)-based optimal output feedback controller, referred to as adaptive critic controller, is proposed for affine nonlinear discrete-time systems, to deliver a desired tracking performance. The adaptive critic design consist of three entities, an observer to estimate the system states, an action network that produces optimal control input and a critic that evaluates the performance of the action network. The critic is termed adaptive as it adapts itself to output the optimal cost-to-go function which is based on the standard Bellman equation. By using the Lyapunov approach, the uniformly ultimate boundedness …

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Neural Network Controller Development And Implementation For Spark Ignition Engines With High Egr Levels, Jonathan B. Vance, Atmika Singh, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier Jan 2007

Neural Network Controller Development And Implementation For Spark Ignition Engines With High Egr Levels, Jonathan B. Vance, Atmika Singh, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier

Electrical and Computer Engineering Faculty Research & Creative Works

Past research has shown substantial reductions in the oxides of nitrogen (NOx) concentrations by using 10% -25% exhaust gas recirculation (EGR) in spark ignition (SI) engines (see Dudek and Sain, 1989). However, under high EGR levels, the engine exhibits strong cyclic dispersion in heat release which may lead to instability and unsatisfactory performance preventing commercial engines to operate with high EGR levels. A neural network (NN)-based output feedback controller is developed to reduce cyclic variation in the heat release under high levels of EGR even when the engine dynamics are unknown by using fuel as the control input. A separate …

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Online Reinforcement Learning Neural Network Controller Design For Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani Jan 2007

Online Reinforcement Learning Neural Network Controller Design For Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel reinforcement learning neural network (NN)-based controller, referred to adaptive critic controller, is proposed for affine nonlinear discrete-time systems with applications to nanomanipulation. In the online NN reinforcement learning method, one NN is designated as the critic NN, which approximates the long-term cost function by assuming that the states of the nonlinear systems is available for measurement. An action NN is employed to derive an optimal control signal to track a desired system trajectory while minimizing the cost function. Online updating weight tuning schemes for these two NNs are also derived. By using the Lyapunov approach, …

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Converting Some Global Optimization Problems To Mixed Integer Linear Problems Using Piecewise Linear Approximations, Manish Kumar Jan 2007

Converting Some Global Optimization Problems To Mixed Integer Linear Problems Using Piecewise Linear Approximations, Manish Kumar

Masters Theses

"Some global optimization problems are converted to mixed-integer linear problems (MILP) using piecewise-linear approximations in this thesis so that they can be solved using commercial MILP solvers, such as CPLEX. Special attention is given to approximating two-term log-sum functions, which appears frequently in generalized geometric programming problems. Numerical results indicate the proposed approach is sound and efficient"--Abstract, page iii.

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Best Practices For Implementing A Biodiesel Program, Sundaresan Sadashivam Jan 2007

Best Practices For Implementing A Biodiesel Program, Sundaresan Sadashivam

Masters Theses

"The Missouri Department of Transportation (MoDOT) has a mandate to utilize biodiesel blends in its fleets. However, they have not been able to meet this requirement due to various implementation issues. Therefore, this thesis presents a study to determine the best practices for implementing a biodiesel program. The study was conducted by soliciting information from Departments of Transportation and other agencies related to their biodiesel programs and practices. A list of best practices was developed and the Analytic Hierarchy Process (AHP) was used to prioritize this list of best practices"--Abstract, page iv.

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Security Architecture Methodology For Large Net-Centric Systems, Njideka Adaku Umeh Jan 2007

Security Architecture Methodology For Large Net-Centric Systems, Njideka Adaku Umeh

Masters Theses

"This thesis describes an over-arching security architecture methodology for large network enabled systems that can be scaled down for smaller network centric operations such as present at the University of Missouri-Rolla. By leveraging the five elements of security policy & standards, security risk management, security auditing, security federation and security management, of the proposed security architecture and addressing the specific needs of UMR, the methodology was used to determine places of improvement for UMR"--Abstract, page iii.

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Use Of Analytical Hierarchy Process In University Strategy Planning, Mihir Gokhale Jan 2007

Use Of Analytical Hierarchy Process In University Strategy Planning, Mihir Gokhale

Masters Theses

"The selection of an appropriate strategy is critical for a university's success, and each university needs to capitalize on its own specialties and competencies for a competitive advantage. Strategy creation and planning in universities is generally a collective effort which relies on consensus. It is a complex process involving the setting of objectives and goals to achieve the strategic vision, and an analysis tool for evaluating and comparing different options and prioritizing objectives and goals is required. A high deductive capacity is necessary for aggregating the different trade-offs while prioritizing, which is challenging for a human mind. This thesis demonstrates …

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Bridge Damage Detection Using An Intelligent Engineering System, Dionysios N. Danilatos Jan 2007

Bridge Damage Detection Using An Intelligent Engineering System, Dionysios N. Danilatos

Masters Theses

"This thesis concerns the design of an algorithm that is capable to detect structural damage in civil infrastructure bridges. The algorithm, which will be dubbed Damage Diagnostics System throughout the thesis, is the software component of a broader Bridge Health Monitoring System. This broader system integrates software and hardware,such as sensors and data acquisition components...The rationale for the Structural Damage Diagnosis is based on the principle of the structural vibration testing. The Health Monitoring System captures the vibration signals, as the bridge responds to excitation from various sources. The purpose of the Diagnostic System is to extract information from the …

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Barriers And Best Practices For Material Management In The Healthcare Sector, Carlos Callender Jan 2007

Barriers And Best Practices For Material Management In The Healthcare Sector, Carlos Callender

Masters Theses

"For many years, the primary focus of the healthcare sector has been to provide patients with the best quality of care. Recently, with the escalating cost of supplies and the severe competition among healthcare providers, the pressure on material managers to operate more cost-efficiently without compromising the high patient care standards has significantly increased. While other sectors have experienced success through the deployment of supply chain management practices, the healthcare sector has not seen major improvements in this area. However, in spite of the uniqueness and complexity of the healthcare supply chain, opportunities for improvements are plentiful. Thus, this thesis …

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Integrated Product And Its Extended Enterprise Network Design Using Lean Principles, Abhijit K. Choudhury Jan 2007

Integrated Product And Its Extended Enterprise Network Design Using Lean Principles, Abhijit K. Choudhury

Masters Theses

"Recently, many system integration companies have begun to intensely focus on suppliers' involvement in the product realization process to enhance their competitiveness. The product architecture has a huge impact on the efficiency of the integrator's supplier network. One of the ways to enhance efficiency is to implement the lean principles while creating a collaborative design/manufacturing/supply chain environment. In this study, two distinct stages of the product realization process, namely, design stage and production stage are considered for determining the design and production supplier networks"--Abstract, page iv.

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Modular Architecting For Effects Based Operations, Emel Meteoglu Jan 2007

Modular Architecting For Effects Based Operations, Emel Meteoglu

Masters Theses

"Effects Based Operations (EBO) is a way of thinking for planning, executing and assessing any operations for the effects they produce, rather than dealing with actions, targets or even objectives. The literature on EBO has been growing day by day; however, there is still a need for modeling techniques and tools that provide more efficient and effective effects based assessment, planning and analysis in order to further develop the capabilities of the operations. In this context, this thesis presents an introduction to EBO by focusing on its methodology, its challenges and also its applicability in different systems. Moreover, this thesis …

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Enhanced Functional Analysis System Technique For Managing Complex Engineering Projects, Sofia Tan Jan 2007

Enhanced Functional Analysis System Technique For Managing Complex Engineering Projects, Sofia Tan

Masters Theses

"This study presents an Enhanced Functional Analysis Systems Technique (EFAST) tool to facilitate communication amongst various stakeholders such as the customers, program managers, systems architects, and systems engineers. the EFAST maps the customer requirements to downstream system functions and subsystem/component requirements, and outlines the interactions between various system and subsystem level and activities using a top-down approach. A bottom-up approach is used to populate the system element cost and time estimates. The EFAST tool compares the budgeted development resources with the estimated development resources to provide a realistic picture for realizing project in terms of performance, cost, and schedule. The …

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Interactive And Dialogue Based Learning In Engineering Education, Siddartha Thummuri Jan 2007

Interactive And Dialogue Based Learning In Engineering Education, Siddartha Thummuri

Masters Theses

"This thesis focuses on a class room architecture that provides high levels of interactivity which enhances the students' learning environment both in distance and on-campus contexts and forms a basis for practical learning. Two analyses are presented in this thesis, the first one being a simple measure of levels of interactivity in this course architecture, based on rubric and the second one, a comparative analysis, to demonstrate the effectiveness of interactive (multi-directional information flow) classrooms as opposed to conventional (unidirectional information flow) classrooms and that this course architecture is ideal for enhancement of distance learning and an excellent route to …

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Executable System Architecting Using Systems Modeling Language In Conjunction With Colored Petri Nets - A Demonstration Using The Geoss Network Centric System, Renzhong Wang Jan 2007

Executable System Architecting Using Systems Modeling Language In Conjunction With Colored Petri Nets - A Demonstration Using The Geoss Network Centric System, Renzhong Wang

Masters Theses

"Models and simulation furnish abstractions to manage complexities allowing engineers to visualize the proposed system and to analyze and validate system behavior before constructing it. Unified Modeling Language (UML) and its systems engineering extension, Systems Modeling Language (SysML), provide a rich set of diagrams for systems specification. However, the lack of executable semantics of such notations limits the capability of analyzing and verifying defined specifications. This research has developed an executable system architecting framework based on SysML-CPN transformation, which introduces dynamic model analysis into SysML modeling by mapping SysML notations to Colored Petri Net (CPN), a graphical language for system …

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Cognitive Biases In Risk Management, William Thomas Siefert Jan 2007

Cognitive Biases In Risk Management, William Thomas Siefert

Masters Theses

"This thesis contends that most Risk Management/Mitigation programs fail to be as effective as they could be due to a number of mostly overlooked drivers, such as motivation and cognitive biases. The issue of cognitive biases is very seldom addressed. When questioned, most engineers purport to not have any biases. They insist that they use only logic, reasoning, and math to make decisions. A set of data was collected and reviewed for this thesis. The data presented shows that cognitive biases do affect the risk management/mitigation process. Knowledge of these biases and their potential impact on a project will lead …

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Asymptotic Stability Of Nonholonomic Mobile Robot Formations Using Multilayer Neural Networks, Jagannathan Sarangapani, Travis Alan Dierks Jan 2007

Asymptotic Stability Of Nonholonomic Mobile Robot Formations Using Multilayer Neural Networks, Jagannathan Sarangapani, Travis Alan Dierks

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers that are widely reported in the literature. A multilayer neural network (NN) is introduced along with robust integral of the sign of the error (RISE) feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are asymptotically stable and the NN weights are bounded as …

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Breaking The Cycle-Preventing Failures By Leveraging Historical Data During Conceptual Design, Daniel A. Krus, Katie Grantham Jan 2007

Breaking The Cycle-Preventing Failures By Leveraging Historical Data During Conceptual Design, Daniel A. Krus, Katie Grantham

Engineering Management and Systems Engineering Faculty Research & Creative Works

Major engineering accidents are often caused by seemingly minor failures propagating through complex systems. One example of this is an accident involving a Bell 206 Rotorcraft where a fuel pump failure led to the severing of the tail boom. Cataloguing and communicating the knowledge of potential failures and failure propagations is critical to prevent further accidents. The need for effective failure prevention tools is not specific to rotorcrafts, however. Failure reporting systems have been adopted by various industries to aid and promote failure prevention. The catalogued failures usually consist of narratives describing which part of a product failed, how it …

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The Development And Application Of A Systematic Approach To Evaluating An Academic Department's Brand Meaning, Cassandra C. Elrod Jan 2007

The Development And Application Of A Systematic Approach To Evaluating An Academic Department's Brand Meaning, Cassandra C. Elrod

Doctoral Dissertations

"Research of existing literature indicates that below the university level, there has been little effort made in branding academia, namely academic departments. The lack of branding may significantly affect the perceptions that potential students and future employers of these students have about one of these academic units. The impact may be most significant for units where the fields of study that are represented by the department may be unclear, such as in the case of engineering management. However, even in the cases of better-understood fields of study, for example, electrical engineering, the competition for students with other fields of study …

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Architecting System Of Systems: Artificial Life Analysis Of Financial Market Behavior, Nil Hande Ergin Jan 2007

Architecting System Of Systems: Artificial Life Analysis Of Financial Market Behavior, Nil Hande Ergin

Doctoral Dissertations

"This research study focuses on developing a framework that can be utilized by system architects to understand the emergent behavior of system architectures. The objective is to design a framework that is modular and flexible in providing different ways of modeling sub-systems of System of Systems. At the same time, the framework should capture the adaptive behavior of the system since evolution is one of the key characteristics of System of Systems. Another objective is to design the framework so that humans can be incorporated into the analysis. The framework should help system architects understand the behavior as well as …

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An Indirect Loss Estimation Methodology To Account For Regional Earthquake Damage To Highway Bridges, Chakkaphan Tirasirichai Jan 2007

An Indirect Loss Estimation Methodology To Account For Regional Earthquake Damage To Highway Bridges, Chakkaphan Tirasirichai

Doctoral Dissertations

"This study proposes an integrated framework to estimate the indirect economic loss due to damaged bridges within the highway system from an earthquake event. The framework is designed to be general and convenient to apply to other study regions. In this dissertation, a simulated earthquake scenario centered in St. Louis Missouri with a magnitude 7.0 was used as a case study. The research results have clearly shown that the indirect losses are significant when compared to the direct loss. Policymakers can apply this study framework and the results as a guide and decision tool for developing an appropriate preventive action …

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Modeling Network Traffic On A Global Network-Centric System With Artificial Neural Networks, Douglas K. Swift Jan 2007

Modeling Network Traffic On A Global Network-Centric System With Artificial Neural Networks, Douglas K. Swift

Doctoral Dissertations

"This dissertation proposes a new methodology for modeling and predicting network traffic. It features an adaptive architecture based on artificial neural networks and is especially suited for large-scale, global, network-centric systems. Accurate characterization and prediction of network traffic is essential for network resource sizing and real-time network traffic management. As networks continue to increase in size and complexity, the task has become increasingly difficult and current methodology is not sufficiently adaptable or scaleable. Current methods model network traffic with express mathematical equations which are not easily maintained or adjusted. The accuracy of these models is based on detailed characterization of …

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Adaptive Critic Neural Network Force Controller For Atomic Force Microscope-Based Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani Oct 2006

Adaptive Critic Neural Network Force Controller For Atomic Force Microscope-Based Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Automating the task of nanomanipulation is extremely important since it is tedious for humans. This paper proposes an atomic force microscope (AFM) based force controller to push nano particles on the substrates. A block phase correlation-based algorithm is embedded into the controller for the compensation of the thermal drift which is considered as the main external uncertainty during nanomanipulation. Then, the interactive forces and dynamics between the tip and the particle, particle and the substrate are modeled and analyzed. Further, an adaptive critic NN controller based on adaptive dynamic programming algorithm is designed and the task of pushing nano particles …

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Neural Network Based Decentralized Excitation Control Of Large Scale Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani Jul 2006

Neural Network Based Decentralized Excitation Control Of Large Scale Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a neural network (NN) based decentralized excitation controller design for large scale power systems. The proposed controller design considers not only the dynamics of generators but also the algebraic constraints of the power flow equations. The control signals are calculated using only local signals. The transient stability and the coordination of the subsystem controllers can be guaranteed. NNs are used to approximate the unknown/imprecise dynamics of the local power system and the interconnections. All signals in the closed loop system are guaranteed to be uniformly ultimately bounded (UUB). Simulation results with a 3-machine power system demonstrate the …

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