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Computer Sciences

2008

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Articles 1 - 23 of 23

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

Neural-Network-Based State Feedback Control Of A Nonlinear Discrete-Time System In Nonstrict Feedback Form, Pingan He, Jagannathan Sarangapani Dec 2008

Neural-Network-Based State Feedback Control Of A Nonlinear Discrete-Time System In Nonstrict Feedback Form, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights ...


Neural Network Output Feedback Control Of A Quadrotor Uav, Jagannathan Sarangapani, Travis Alan Dierks Dec 2008

Neural Network Output Feedback Control Of A Quadrotor Uav, Jagannathan Sarangapani, Travis Alan Dierks

Electrical and Computer Engineering Faculty Research & Creative Works

A neural network (NN) based output feedback controller for a quadrotor unmanned aerial vehicle (UAV) is proposed. The NNs are utilized in the observer and for generating virtual and actual control inputs, respectively, where the NNs learn the nonlinear dynamics of the UAV online including uncertain nonlinear terms like aerodynamic friction and blade flapping. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semi-globally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional ...


A Model Based Fault Detection And Prognostic Scheme For Uncertain Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani Dec 2008

A Model Based Fault Detection And Prognostic Scheme For Uncertain Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A new fault detection and prognostics (FDP) framework is introduced for uncertain nonlinear discrete time system by using a discrete-time nonlinear estimator which consists of an online approximator. A fault is detected by monitoring the deviation of the system output with that of the estimator output. Prior to the occurrence of the fault, this online approximator learns the system uncertainty. In the event of a fault, the online approximator learns both the system uncertainty and the fault dynamics. A stable parameter update law in discrete-time is developed to tune the parameters of the online approximator. This update law is also ...


Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau Dec 2008

Distributing Complementary Resources Across Multiple Periods With Stochastic Demand, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Research Collection School Of Information Systems

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments, we show that under stochastic conditions the performance variation of the process decreases as the time frame length (time ...


Leading Firms As Knowledge Gatekeepers In A Networked Environment, Deogratias Harorimana Mr Nov 2008

Leading Firms As Knowledge Gatekeepers In A Networked Environment, Deogratias Harorimana Mr

Dr Deogratias Harorimana

This chapter introduces the role of the knowledge gatekeeper as a mechanism by which knowledge is created and transferred in a networked environment. Knowledge creation and transfer are essential for building a knowledge based economy. The chapter considers obstacles that inhibit this process and argues that leading firms create a shared socio-cultural context that enables the condivision of tacit meanings and codification of knowledge. Leading firms act as gatekeepers of knowledge through the creation of shared virtual platforms. There will be a leading firm that connects several networks of clients and suppliers may not interact directly with one another, but ...


A Model Based Fault Detection Scheme For Nonlinear Multivariable Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani Oct 2008

A Model Based Fault Detection Scheme For Nonlinear Multivariable Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel robust scheme is developed for detecting faults in nonlinear discrete time multi-input and multi-output systems in contrast with the available schemes that are developed in continuous-time. Both state and output faults are addressed by considering separate time profiles. The faults, which could be incipient or abrupt, are modeled using input and output signals of the system. By using nonlinear estimation techniques, the discrete-time system is monitored online. Once a fault is detected, its dynamics are characterized using an online approximator. A stable parameter update law is developed for the online approximator scheme in discrete-time. The ...


Spreadsheet Data Resampling For Monte-Carlo Simulation, Thin Yin Leong, Wee Leong Lee Oct 2008

Spreadsheet Data Resampling For Monte-Carlo Simulation, Thin Yin Leong, Wee Leong Lee

Research Collection School Of Information Systems

The pervasiveness of spreadsheets software resulted in its increased application as a simulation tool for business analysis. Random values generation supporting such evaluations using spreadsheets are simple and yet powerful. However, the typical approach to Monte-Carlo simulations, which is what simulations with stochasticity are called, requires significant amount of time to be spent on data collection, data collation, and distribution function fitting. In fact, the latter can be overwhelming for undergraduate students to learn and do properly in a short time. Resampling eliminates both the need to fit distributions to the sample data, and to perform the ensuing tests of ...


Optimal Energy-Delay Routing Protocol With Trust Levels For Wireless Ad Hoc Networks, Eyad Taqieddin, Ann K. Miller, Jagannathan Sarangapani Sep 2008

Optimal Energy-Delay Routing Protocol With Trust Levels For Wireless Ad Hoc Networks, Eyad Taqieddin, Ann K. Miller, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the Trust Level Routing (TLR) pro- tocol, an extension of the optimized energy-delay rout- ing (OEDR) protocol, focusing on the integrity, reliability and survivability of the wireless network. TLR is similar to OEDR in that they both are link state routing proto- cols that run in a proactive mode and adopt the concept of multi-point relay (MPR) nodes. However, TLR aims at incorporating trust levels into routing by frequently changing the MPR nodes as well as authenticating the source node and contents of control packets. TLR calcu- lates the link costs based on a composite metric (delay ...


A Heuristic Method For Job-Shop Scheduling With An Infinite Wait Buffer: From One-Machine To Multi-Machine Problems, Z. J. Zhao, J. Kim, M. Luo, Hoong Chuin Lau, S. S. Ge Sep 2008

A Heuristic Method For Job-Shop Scheduling With An Infinite Wait Buffer: From One-Machine To Multi-Machine Problems, Z. J. Zhao, J. Kim, M. Luo, Hoong Chuin Lau, S. S. Ge

Research Collection School Of Information Systems

Through empirical comparison of classical job shop problems (JSP) with multi-machine consideration, we find that the objective to minimize the sum of weighted tardiness has a better wait property compared with the objective to minimize the makespan. Further, we test the proposed Iterative Minimization Micro-model (IMM) heuristic method with the mixed integer programming (MIP) solution by CPLEX. For multi-machine problems, the IMM heuristic method is faster and achieves a better solution. Finally, for a large problem instance with 409 jobs and 30 types of machines, IMM-heuristic method is compared with ProModel and we find that the heuristic method is slightly ...


Generating Robust Schedules Subject To Resource And Duration Uncertainties, Na Fu, Hoong Chuin Lau, Fei Xiao Sep 2008

Generating Robust Schedules Subject To Resource And Duration Uncertainties, Na Fu, Hoong Chuin Lau, Fei Xiao

Research Collection School Of Information Systems

We consider the Resource-Constrained Project Scheduling Problem with minimal and maximal time lags under resource and duration uncertainties. To manage resource uncertainties, we build upon the work of Lambrechts et al 2007 and develop a method to analyze the effect of resource breakdowns on activity durations. We then extend the robust local search framework of Lau et al 2007 with additional considerations on the impact of unexpected resource breakdowns to the project makespan, so that partial order schedules (POS) can absorb both resource and duration uncertainties. Experiments show that our proposed model is capable of addressing the uncertainty of resources ...


Modeling Of Fermentation Processes Using Online Kernel Learning Algorithm, Yi Liu Jul 2008

Modeling Of Fermentation Processes Using Online Kernel Learning Algorithm, Yi Liu

Dr. Yi Liu

No abstract provided.


Adaptive Control Of A Class Of Nonlinear Discrete-Time Systems With Online Kernel Learning, Yi Liu Jul 2008

Adaptive Control Of A Class Of Nonlinear Discrete-Time Systems With Online Kernel Learning, Yi Liu

Dr. Yi Liu

No abstract provided.


Damping Inter-Area Oscillations By Upfcs Based On Selected Global Measurements, Mahyar Zarghami, Yilu Liu, Jagannathan Sarangapani, Mariesa Crow Jul 2008

Damping Inter-Area Oscillations By Upfcs Based On Selected Global Measurements, Mahyar Zarghami, Yilu Liu, Jagannathan Sarangapani, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a method of using a selected set of the global data for controlling inter-area oscillations of the power network using unified power flow controllers. This novel algorithm utilizes reduced order observers for estimating the missing data the purpose of control when all the data is unavailable through frequency measurements in a wide area control approach. The paper will also address the problem of time-delay in data acquisition through examples.


Biology-Inspired Approach For Communal Behavior In Massively Deployed Sensor Networks, Kennie H. Jones Jul 2008

Biology-Inspired Approach For Communal Behavior In Massively Deployed Sensor Networks, Kennie H. Jones

Computer Science Theses & Dissertations

Research in wireless sensor networks has accelerated rapidly in recent years. The promise of ubiquitous control of the physical environment opens the way for new applications that will redefine the way we live and work. Due to the small size and low cost of sensor devices, visionaries promise smart systems enabled by deployment of massive numbers of sensors working in concert. To date, most of the research effort has concentrated on forming ad hoc networks under centralized control, which is not scalable to massive deployments. This thesis proposes an alternative approach based on models inspired by biological systems and reports ...


Linear Relaxation Techniques For Task Management In Uncertain Settings, Pradeep Varakantham, Stephen F. Smith Jul 2008

Linear Relaxation Techniques For Task Management In Uncertain Settings, Pradeep Varakantham, Stephen F. Smith

Research Collection School Of Information Systems

In this paper, we consider the problem of assisting a busy user in managing her workload of pending tasks. We assume that our user is typically oversubscribed, and is invariably juggling multiple concurrent streams of tasks (or work flows) of varying importance and urgency. There is uncertainty with respect to the duration of a pending task as well as the amount of follow-on work that may be generated as a result of executing the task. The user’s goal is to be as productive as possible; i.e., to execute tasks that realize the maximum cumulative payoff. This is achieved ...


Missouri S&T Mote-Based Demonstration Of Energy Monitoring Solution For Network Enabled Manufacturing Using Wireless Sensor Networks (Wsn), James W. Fonda, Maciej Jan Zawodniok, Al Salour, Jagannathan Sarangapani, Donald Miller Apr 2008

Missouri S&T Mote-Based Demonstration Of Energy Monitoring Solution For Network Enabled Manufacturing Using Wireless Sensor Networks (Wsn), James W. Fonda, Maciej Jan Zawodniok, Al Salour, Jagannathan Sarangapani, Donald Miller

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, an inexpensive electric utilities monitoring solution using wireless sensor networks is demonstrated that can easily be installed, deployed, maintained and eliminate unnecessary energy costs and effort. The monitoring solution is designed to support network enabled manufacturing (NEM) program using Missouri University of Science and Technology (MST), formerly the University of Missouri-Rolla (UMR), motes.


Output Feedback Controller For Operation Of Spark Ignition Engines At Lean Conditions Using Neural Networks, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier Mar 2008

Output Feedback Controller For Operation Of Spark Ignition Engines At Lean Conditions Using Neural Networks, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier

Electrical and Computer Engineering Faculty Research & Creative Works

Spark ignition (SI) engines operating at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle bifurcation of heat release. Past literature suggests that operating an engine under such lean conditions can significantly reduce NO emissions by as much as 30% and improve fuel efficiency by as much as 5%-10%. At lean conditions, the heat release per engine cycle is not close to constant, as it is when these engines operate under stoichiometric conditions where the equivalence ratio is 1.0. A neural network controller employing output feedback has shown ability in simulation to reduce the nonlinear cyclic dispersion ...


A Suite Of Robust Controllers For The Manipulation Of Microscale Objects, Qinmin Yang, Jagannathan Sarangapani Feb 2008

A Suite Of Robust Controllers For The Manipulation Of Microscale Objects, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A suite of novel robust controllers is introduced for the pickup operation of microscale objects in a microelectromechanical system (MEMS). In MEMS, adhesive, surface tension, friction, and van der Waals forces are dominant. Moreover, these forces are typically unknown. The proposed robust controller overcomes the unknown contact dynamics and ensures its performance in the presence of actuator constraints by assuming that the upper bounds on these forces are known. On the other hand, for the robust adaptive critic-based neural network (NN) controller, the unknown dynamic forces are estimated online. It consists of an action NN for compensating the unknown system ...


Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility Design, Yitung Chen, Sean Hsieh Jan 2008

Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility Design, Yitung Chen, Sean Hsieh

Separations Campaign (TRP)

The major objectives will lead to the creation of a framework that combines all the strengths of AMUSE’s complicated calculations, well-established commercial system process package, and ISOPro’s flexible parameter optimization modules. Development of the process simulation code can be done using the solvent extraction process at Argonne National Laboratory in collaboration with the research team from the Mechanical Engineering Department at UNLV.

Research accomplishments:

• Completed final version of the ISOPro User Manual associated with summarized ISOPro source codes.

• Redesigned and completed use case and design class diagrams (DCD) of the ISOPro package using ArgoUML.

• Improved ISOPro system and ...


A Web-Based Environment For Documentation And Sharing Of Engineering Design Knowledge, Justin A. Rockwell, Paul Witherell, Rui Fernandes, Ian R. Grosse, Sundar Krishnamurty, Jack C. Wileden Jan 2008

A Web-Based Environment For Documentation And Sharing Of Engineering Design Knowledge, Justin A. Rockwell, Paul Witherell, Rui Fernandes, Ian R. Grosse, Sundar Krishnamurty, Jack C. Wileden

Center for e-Design Proceedings

This paper presents the foundation for a collaborative Web-based environment for improving communication by formally defining a platform for documentation and sharing of engineering design knowledge throughout the entire design process. In this work an ontological structure is utilized to concisely define a set of individual engineering concepts. This set of modular ontologies link together to create a flexible, yet consistent, product development knowledge-base. The resulting infrastructure uniquely enables the information stored within the knowledge-base to be readily inspectable and computable, thus allowing for design tools that reason on the information to assist designers and automate design processes. A case ...


Generalized Hamilton-Jacobi-Bellman Formulation-Based Neural Network Control Of Affine Nonlinear Discrete-Time Systems, Zheng Chen, Jagannathan Sarangapani Jan 2008

Generalized Hamilton-Jacobi-Bellman Formulation-Based Neural Network Control Of Affine Nonlinear Discrete-Time Systems, Zheng Chen, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we consider the use of nonlinear networks towards obtaining nearly optimal solutions to the control of nonlinear discrete-time (DT) systems. The method is based on least squares successive approximation solution of the generalized Hamilton-Jacobi-Bellman (GHJB) equation which appears in optimization problems. Successive approximation using the GHJB has not been applied for nonlinear DT systems. The proposed recursive method solves the GHJB equation in DT on a well-defined region of attraction. The definition of GHJB, pre-Hamiltonian function, HJB equation, and method of updating the control function for the affine nonlinear DT systems under small perturbation assumption are proposed ...


The Oil Drilling Model And Iterative Deepening Genetic Annealing Algorithm For The Traveling Salesman Problem, Hoong Chuin Lau, Fei Xiao Jan 2008

The Oil Drilling Model And Iterative Deepening Genetic Annealing Algorithm For The Traveling Salesman Problem, Hoong Chuin Lau, Fei Xiao

Research Collection School Of Information Systems

In this work, we liken the solving of combinatorial optimization problems under a prescribed computational budget as hunting for oil in an unexplored ground. Using this generic model, we instantiate an iterative deepening genetic annealing (IDGA) algorithm, which is a variant of memetic algorithms. Computational results on the traveling salesman problem show that IDGA is more effective than standard genetic algorithms or simulated annealing algorithms or a straightforward hybrid of them. Our model is readily applicable to solve other combinatorial optimization problems.


Ethnic-Identity Intensity As A Moderator Of The Technology Acceptance Model And Its Antecedents, Marcus Anthony Alexander Jan 2008

Ethnic-Identity Intensity As A Moderator Of The Technology Acceptance Model And Its Antecedents, Marcus Anthony Alexander

Retrospective Theses and Dissertations

The goal of this dissertation is oriented to study the motivation of minorities to adopt and learn new, innovative technologies. The primary research question: is there some reason the African-American experience is driving certain sub-groups of the population to the wrong side of the digital divide? To examine this, I introduce ethnic identity as a moderating variable to a leftward extended technology acceptance model (TAM). Additionally, both components of the classic TAM (ease of use and usefulness) are divided into two antecedents: (1) ease of use - (a) trait efficacy and (b) state efficacy and (2) usefulness (completely replaced by) - (a ...