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Missouri University of Science and Technology

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Articles 661 - 690 of 846

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

Design Stability, K. M. Ragsdell Jan 2005

Design Stability, K. M. Ragsdell

Engineering Management and Systems Engineering Faculty Research & Creative Works

Design for Six Sigma (DFSS) is a quality management strategy, which shows promise for manufacturing organizations, which seek to rapidly develop and market high-quality, low-cost products for hyper-competitive markets. This paper introduces and discusses the concept of design stability, and its relationship to reliability, durability and warranty cost. the use of this concept at very early stages of product development, even before knowledge of customer preferences, is discussed. the use of the design stability concept as a part of DFSS is suggested as an effective supply chain management strategy. Copyright © 2005 SAE International.

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Neural Network -Based Nearly Optimal Hamilton-Jacobi-Bellman Solution For Affine Nonlinear Discrete-Time Systems, Jagannathan Sarangapani, Zheng Chen Jan 2005

Neural Network -Based Nearly Optimal Hamilton-Jacobi-Bellman Solution For Affine Nonlinear Discrete-Time Systems, Jagannathan Sarangapani, Zheng Chen

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 systems. The method is based on least-squares successive approximation solution of the Generalized Hamilton-Jacobi-Bellman (HJB) equation. Since successive approximation using the GHJB has not been applied for nonlinear discrete-time systems, the proposed recursive method solves the GHJB equation in discrete-time 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 discrete time systems are proposed. A neural network is used to approximate the GHJB …

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Neural Network-Based Control Of Nonlinear Discrete-Time Systems In Non-Strict Form, Jagannathan Sarangapani, Zheng Chen, Pingan He Jan 2005

Neural Network-Based Control Of Nonlinear Discrete-Time Systems In Non-Strict Form, Jagannathan Sarangapani, Zheng Chen, Pingan He

Electrical and Computer Engineering Faculty Research & Creative Works

A novel reinforcement learning-based adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to deliver a desired tracking performance for a class of non-strict feedback nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The adaptive critic NN controller architecture includes a critic NN and two action NNs. The critic NN approximates certain strategic utility function whereas the action neural networks are used to minimize both the strategic utility function and the unknown dynamics estimation errors. The NN weights are tuned online so as to minimize certain performance index. By using gradient descent-based …

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Energy-Efficient Rate Adaptation Mac Protocol For Ad Hoc Wireless Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani Jan 2005

Energy-Efficient Rate Adaptation Mac Protocol For Ad Hoc Wireless Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Resource constraints in ad hoc wireless networks require that they are energy efficient during both transmission and rate adaptation. In this paper, we propose a novel energy-efficient rate adaptation protocol that selects modulation schemes online to maximize throughput based on channel state while saving energy. This protocol uses the distributed power control (DPC) algorithm (M. Zawodniok et al., 2004) to accurately determine the necessary transmission power and to reduce the energy consumption. Additionally, the transmission rate is altered using energy efficiency as a constraint to meet the required throughput, which is estimated with queue fill ratio. Moreover, back-off scheme is …

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A Robust Controller For The Manipulation Of Micro Scale Objects, Qinmin Yang, Jagannathan Sarangapani Jan 2005

A Robust Controller For The Manipulation Of Micro Scale Objects, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A suite of novel robust controllers is presented for the manipulation and handling of micro-scale objects in a micro-electromechanical system (MEMS) where adhesive, surface tension, friction and van der Waals forces are dominant. Moreover, these forces are typically unknown. The robust controller overcomes the unknown system dynamics and ensures the 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 controller, the unknown forces are estimated online. Using the Lyapunov approach, the uniformly ultimate boundedness (UUB) of the closed-loop manipulation error is shown for …

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Predictive Congestion Control Mac Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani Jan 2005

Predictive Congestion Control Mac Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks results in a large number of packet drops, unfairness with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, a suite of novel, decentralized, predictive congestion control schemes are proposed for wireless sensor networks in concert with distributed power control (DPC). Besides providing energy efficient solution, embedded channel estimator in DPC predicts the channel quality. By using the channel quality and node queue utilizations, the onset of network congestion is predicted and congestion control is initiated. …

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Decentralized Discrete-Time Neural Network Controller For A Class Of Nonlinear Systems With Unknown Interconnections, Jagannathan Sarangapani Jan 2005

Decentralized Discrete-Time Neural Network Controller For A Class Of Nonlinear Systems With Unknown Interconnections, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel decentralized neural network (NN) controller in discrete-time is designed for a class of uncertain nonlinear discrete-time systems with unknown interconnections. Neural networks are used to approximate both the uncertain dynamics of the nonlinear systems and the unknown interconnections. Only local signals are needed for the decentralized controller design and the stability of the overall system can be guaranteed using the Lyapunov analysis. Further, controller redesign for the original subsystems is not required when additional subsystems are appended. Simulation results demonstrate the effectiveness of the proposed controller. The NN does not require an offline learning phase and the weights …

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Block Phase Correlation-Based Automatic Drift Compensation For Atomic Force Microscopes, Qinmin Yang, Eric W. Bohannan, Jagannathan Sarangapani Jan 2005

Block Phase Correlation-Based Automatic Drift Compensation For Atomic Force Microscopes, Qinmin Yang, Eric W. Bohannan, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Automatic nanomanipulation and nanofabrication with an Atomic Force Microscope (AFM) is a precursor for nanomanufacturing. In ambient conditions without stringent environmental controls, nanomanipulation tasks require extensive human intervention to compensate for the many spatial uncertainties of the AFM. Among these uncertainties, thermal drift is especially hard to solve because it tends to increase with time and cannot be compensated simultaneously by feedback. In this paper, an automatic compensation scheme is introduced to measure and estimate drift. This information can be subsequently utilized to compensate for the thermal drift so that a real-time controller for nanomanipulation can be designed as if …

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Special Session - Team Training To Promote Constructive (Not Destructive) Conflict, Ray Luechtefeld, Steve Eugene Watkins Jan 2005

Special Session - Team Training To Promote Constructive (Not Destructive) Conflict, Ray Luechtefeld, Steve Eugene Watkins

Engineering Management and Systems Engineering Faculty Research & Creative Works

Advancing technology increases the need for engineering students to perform effectively on multidisciplinary teams. While conflict is a normal, and even necessary, component of team dynamics, if not managed effectively it can lead to destructive (rather than constructive) outcomes. An Action Science approach to group and individual effectiveness can help teams handle conflict constructively. This session uses a "Teach the Teacher" approach to give participants a basic understanding of skills underlying the approach. It provides practice in Action Science through a set of learning modules. These skills can be brought back and integrated into the participants' courses to provide student …

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Taxonomy Of Systems-Of-Systems, James Gideon, Cihan H. Dagli, Ann K. Miller Jan 2005

Taxonomy Of Systems-Of-Systems, James Gideon, Cihan H. Dagli, Ann K. Miller

Engineering Management and Systems Engineering Faculty Research & Creative Works

The study of systems-of-systems is an increasingly important topic in systems engineering. Though there is not complete agreement, a more precise definition of what these highly evolved systems are and what attributes they possess has certainly emerged. However, there are still areas in the study where the topic can be advanced by a more rigorous presentation of the basic elements. One such area is the taxonomy of systems-ofsystems. This paper will begin with the definition of systems-of-systems as it currently stands and will present the taxonomy from a broader view with additional considerations for classification. These taxonomic categories will consider …

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A "Theory Of Action" Perspective On Effective Organizational Change, Ray Luechtefeld Jan 2005

A "Theory Of Action" Perspective On Effective Organizational Change, Ray Luechtefeld

Engineering Management and Systems Engineering Faculty Research & Creative Works

No abstract provided.

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A Generic, Adaptive Systems Engineering Information Model I, Ann K. Miller, Joseph J. Simpson, Scott Erwin Grasman, Cihan H. Dagli Jan 2005

A Generic, Adaptive Systems Engineering Information Model I, Ann K. Miller, Joseph J. Simpson, Scott Erwin Grasman, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper proposes a new network centric architecture that can be used by first responders to effectively respond to crisis situations. The powerful network-centric concept originally developed for and mainly used in the military environment, can be effectively used for civilian security and emergency response missions. This paper also proposes the use of a swarm of intelligent robots as a part of the network-centric architecture to aid the first responders. The swarm of robots works in tandem with the first responders and provides them with the necessary information on a real time basis. The proposed network centric architecture with a …

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An Sds Modeling Approach For Simulation-Based Control, Sreeram Ramakrishnan, Kumar Mayur Thakur Jan 2005

An Sds Modeling Approach For Simulation-Based Control, Sreeram Ramakrishnan, Kumar Mayur Thakur

Engineering Management and Systems Engineering Faculty Research & Creative Works

We initiate a study of mathematical models for specifying (discrete) simulation-based control systems. It is desirable to specify simulation-based control systems using a model that is intuitive, succinct, expressive, and whose state space properties are relatively easy computationally. We compare automata-based models for specifying control systems and find that all systems that are currently used (such as finite state machines, communicating hierarchical finite state machines (FSM), communicating finite state machines, and Turing machines) lack at least one of the abovementioned features. We propose using sequential dynamical systems (SDS) - a formalism for representing discrete simulations - to specify simulation-based control …

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Network-Centric First Responder Architecture With Swarming Robots Entity, Lakshmanan Meyyappan, Cihan H. Dagli Jan 2005

Network-Centric First Responder Architecture With Swarming Robots Entity, Lakshmanan Meyyappan, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper proposes a new network centric architecture that can be used by first responders to effectively respond to crisis situations. The powerful network-centric concept originally developed for and mainly used in the military environment, can be effectively used for civilian security and emergency response missions. This paper also proposes the use of a swarm of intelligent robots as a part of the network-centric architecture to aid the first responders. The swarm of robots works in tandem with the first responders and provides them with the necessary information on a real time basis. The proposed network centric architecture with a …

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Feedback Linearization Based Power System Stabilizer Design With Control Limits, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Jagannathan Sarangapani Aug 2004

Feedback Linearization Based Power System Stabilizer Design With Control Limits, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In power system controls, simplified analytical models are used to represent the dynamics of power system and controller designs are not rigorous with no stability analysis. One reason is because the power systems are complex nonlinear systems which pose difficulty for analysis. This paper presents a feedback linearization based power system stabilizer design for a single machine infinite bus power system. Since practical operating conditions require the magnitude of control signal to be within certain limits, the stability of the control system under control limits is also analyzed. Simulation results under different kinds of operating conditions show that the controller …

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Successfully Blending Distance Students Into The On-Campus Classroom, Susan L. Murray, David Lee Enke, Sreeram Ramakrishnan Jun 2004

Successfully Blending Distance Students Into The On-Campus Classroom, Susan L. Murray, David Lee Enke, Sreeram Ramakrishnan

Engineering Management and Systems Engineering Faculty Research & Creative Works

As universities are increasingly embracing distance education technology, it is useful to examine the challenges and opportunities of technology in the classroom. This is especially true when the course contains on-campus local students in addition to students learning at a distance. A significant challenge commonly faced is how to remain flexible in presenting course materials while still having notes and other handouts in electronic format available before the lecture. Other challenges include creating and using lecture material that can be viewed at low resolution and low bandwidth, and getting distance students to interact with the instructor, on-campus students, and fellow …

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Discrete-Time Neural Network Output Feedback Control Of Nonlinear Systems In Non-Strict Feedback Form, Pingan He, Jagannathan Sarangapani Jan 2004

Discrete-Time Neural Network Output Feedback Control Of Nonlinear Systems In Non-Strict Feedback Form, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

An adaptive neural network (NN)-based output feedback controller is proposed to deliver a desired tracking performance for a class of discrete-time nonlinear systems, which is represented in non-strict feedback form. The NN backstepping approach is utilized to design the adaptive output feedback controller consisting of: 1) a NN observer to estimate the system states with the input-output data, and 2) two NNs to generate the virtual and actual control inputs, respectively. The non-causal problem in the discrete-time backstepping design is avoided by using the universal NN approximator. The persistence excitation (PE) condition is relaxed both in the NN observer and …

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Neural Network Controller For Manipulation Of Micro-Scale Objects, Vijayakumar Janardhan, Pingan He, Jagannathan Sarangapani Jan 2004

Neural Network Controller For Manipulation Of Micro-Scale Objects, Vijayakumar Janardhan, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel reinforcement learning-based neural network (RLNN) controller is presented for the manipulation and handling of micro-scale 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 RLNN controller consists of an action NN for compensating the unkoown system dynamics, and a critic NN to tune the weights of the action NN. Using the Lyapunov approach, the uniformly ultimate houndedness (UUB) of the closed-loop tracking error and weight estimates are shown by using a novel weight updates. Simulation results are presented to substantiate the …

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Adaptive Force-Balancing Control Of Mems Gyroscope With Actuator Limits, Mohammed Hameed, Jagannathan Sarangapani Jan 2004

Adaptive Force-Balancing Control Of Mems Gyroscope With Actuator Limits, Mohammed Hameed, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This work presents an adaptive force-balancing control (AFBC) scheme with actuator limits for a MEMS Z-axis gyroscope. The purpose of the adaptive force-balancing control is to identify major fabrication imperfections so that they are properly compensated unlike the case of conventional force-balancing controlled gyroscope. The proposed AFBC scheme controls the vibratory modes of the proof mass while ensuring that the control input satisfies the magnitude constraints and the performance of the gyroscope is enhanced in the presence of fabrication uncertainties. Consequently, commonly reported problems of MEMS gyroscope such as quadrature compensation, drive and sense axes frequency tuning are not needed …

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Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow Jan 2004

Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

A novel decentralized neural network (DNN) controller is proposed for a class of large-scale nonlinear systems with unknown interconnections. The objective is to design a DNN for a class of large-scale systems which do not satisfy the matching condition requirement. The NNs are used to approximate the unknown subsystem dynamics and the interconnections. The DNN is designed using the back stepping methodology with only local signals for feedback. All of the signals in the closed loop (system states and weights estimation errors) are guaranteed to be uniformly ultimately bounded and eventually converge to a compact set.

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A Distributed Power Control Mac Protocol For Wireless Ad-Hoc Networks., Maciej Jan Zawodniok, Jagannathan Sarangapani Jan 2004

A Distributed Power Control Mac Protocol For Wireless Ad-Hoc Networks., Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel distributed power control (DPC)⋅ scheme and a MAC protocol for wireless ad hoc networks in the presence of radio channel uncertainties such as path loss, Shadowing and Rayleigh fading is presented. The DPC quickly estimates the time-varying nature of the channel and uses the information to select a suitable transmitter power value in order to maintain a target Signal-to-Interference ratio (SIR) at the receiver. The standard assumption of a constant interference during a link's power update used in other works is relaxed. The performance of the proposed DPC is demonstrated analytically. The power used for all RTS-CTS-DATA-ACK frames …

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Adaptive Critic Neural Network-Based Object Grasping Control Using A Three-Finger Gripper, Gustavo Galan, Jagannathan Sarangapani Jan 2004

Adaptive Critic Neural Network-Based Object Grasping Control Using A Three-Finger Gripper, Gustavo Galan, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Grasping of objects has been a challenging task for robots. The complex grasping task can be defined as object contact control and manipulation subtasks. In this paper, object contact control subtask is defined as the ability to follow a trajectory accurately by the fingers of a gripper. The object manipulation subtask is defined in terms of maintaining a predefined applied force by the fingers on the object. A sophisticated controller is necessary since the process of grasping an object without a priori knowledge of the object's size, texture, softness, gripper, and contact dynamics is rather difficult. Moreover, the object has …

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Forecasting Series-Based Stock Price Data Using Direct Reinforcement Learning, H. Li, Cihan H. Dagli, David Lee Enke Jan 2004

Forecasting Series-Based Stock Price Data Using Direct Reinforcement Learning, H. Li, Cihan H. Dagli, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

A significant amount of work has been done in the area of price series forecasting using soft computing techniques, most of which are based upon supervised learning. Unfortunately, there has been evidence that such models suffer from fundamental drawbacks. Given that the short-term performance of the financial forecasting architecture can be immediately measured, it is possible to integrate reinforcement learning into such applications. In this paper, we present the novel hybrid view for a financial series and critic adaptation stock price forecasting architecture using direct reinforcement. A new utility function called policies-matching ratio is also proposed. The need for the …

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Cost Allocation For Transmission Investment Using Agent-Based Game Theory, Jakapun Mepokee, David Lee Enke, Badrul H. Chowdhury Jan 2004

Cost Allocation For Transmission Investment Using Agent-Based Game Theory, Jakapun Mepokee, David Lee Enke, Badrul H. Chowdhury

Engineering Management and Systems Engineering Faculty Research & Creative Works

Due to electrical power restructuring, a dramatic change has been made to the generation and transmission sectors of the power industry. Rules and legislation are continuously changing. To promote more competition, transmission has to be expanded or upgraded to remove congestion and market power. The cost allocation of new investment in transmission has to be recalculated. The socialization methods of the past have been shown to be unfair to some market and network participants. The decentralization of cost allocation must be considered. The proposed paper provides a comparison between traditional cost allocation methods and a new cost allocation method based …

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Discerning Attributes Which Stimulate Performance In Quality Improvement Teams, Dwan Lamar Prude Jan 2004

Discerning Attributes Which Stimulate Performance In Quality Improvement Teams, Dwan Lamar Prude

Masters Theses

"Total quality management (TQM) can be summed up as people and the way they work. One key element of the philosophies of TQM is the heavy emphasis on utilizing quality improvement teams (QITs) and quality tools to effectively create high performance organizations. Specifically, this investigation asks the following questions: 1) What are the key attributes that contribute to performance in QITs? 2) What is the relationship between team communication and QIT performance? 3) What is the relationship between the number of quality tools utilized in a team and QIT performance? Participants for this study were 101 students from the University …

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Understanding Market Stakeholder Perspectives: Application In The Biopharmaceutical Industry, Halvard Nystrom, Kalayanee Poon-Asawasombat Jun 2003

Understanding Market Stakeholder Perspectives: Application In The Biopharmaceutical Industry, Halvard Nystrom, Kalayanee Poon-Asawasombat

Engineering Management and Systems Engineering Faculty Research & Creative Works

New products are sometimes perceived as risky. This article contributes a process that new product development teams can use to better understand stakeholders' concerns. the stakeholder analysis process is appropriate for products that can be perceived as risky since it enables developers to address key issues of concern prior to new product introduction, mitigating market acceptance risk. It uses a stakeholder model that facilitates dialogue to understand market risks and guide the assessment process. This article includes a case study describing a successful application of introducing biopharmaceutical products, as well as some of the key findings to demonstrate usefulness. © …

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Neuro Emission Controller For Minimizing Cyclic Dispersion In Spark Ignition Engines, Pingan He, Jagannathan Sarangapani Jan 2003

Neuro Emission Controller For Minimizing Cyclic Dispersion In Spark Ignition Engines, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel neural network (NN) controller is developed to control spark ignition (SI) engines at extreme lean conditions. The purpose of neurocontroller is to reduce the cyclic dispersion at lean operation even when the engine dynamics are unknown. The stability analysis of the closed-loop control system is given and the boundedness of all signals is ensured. Results demonstrate that the cyclic dispersion is reduced significantly using the proposed controller. The neuro controller can also be extended to minimize engine emissions with high EGR levels, where similar complex cyclic dynamics are observed. Further, the proposed approach can be applied to control …

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Rate-Based End-To-End Congestion Control Of Multimedia Traffic In Packet Switched Networks, Mingsheng Peng, S. R. Subramanya, Jagannathan Sarangapani Jan 2003

Rate-Based End-To-End Congestion Control Of Multimedia Traffic In Packet Switched Networks, Mingsheng Peng, S. R. Subramanya, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes an explicit rate-based end-to-end congestion control mechanism to alleviate congestion of multimedia traffic in packet switched networks such as the Internet. The congestion is controlled by adjusting the transmission rates of the sources in response to the feedback information from destination such as the buffer occupancy, packet arrival rate and service rate at the outgoing link, so that a desired quality of service (QoS) can be met. The QoS is defined in terms of packet loss ratio, transmission delay, power, and network utilization. Comparison studies demonstrate the effectiveness of the proposed scheme over New-Reno TCP (a variant …

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Nonlinear Time Series Prediction By Weighted Vector Quantization, Amaury Lendasse, D. Francois, V. Wertz, M. Verleysen Jan 2003

Nonlinear Time Series Prediction By Weighted Vector Quantization, Amaury Lendasse, D. Francois, V. Wertz, M. Verleysen

Engineering Management and Systems Engineering Faculty Research & Creative Works

Classical Nonlinear Models for Time Series Prediction Exhibit Improved Capabilities Compared to Linear Ones. Nonlinear Regression Has However Drawbacks, Such as overfilling and Local Minima Problems, User-Adjusted Parameters, Higher Computation Times, Etc. There is Thus a Need for Simple Nonlinear Models with a Restricted Number of Learning Parameters, High Performances and Reasonable Complexity. in This Paper, We Present a Method for Nonlinear Forecasting based on the Quantization of Vectors Concatenating Inputs (Regressors) and Outputs (Predictions). Weighting Techniques Are Applied to Give More Importance to Inputs and Outputs Respectively. the Method is Illustrated on Standard Time Series Prediction Benchmarks. © Springer-Verlag …

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Software Development In The Grid: The Damien Tool-Set, Edgar Gabriel, Rainer Keller, Peggy Lindner, Matthias S. Müller, Michael M. Resch Jan 2003

Software Development In The Grid: The Damien Tool-Set, Edgar Gabriel, Rainer Keller, Peggy Lindner, Matthias S. Müller, Michael M. Resch

Engineering Management and Systems Engineering Faculty Research & Creative Works

The development of applications for Grid-environments is currently lacking the support of tools, which end-users are familiar with from their regular working environment. This paper analyzes the requirements for developing, porting and optimizing scientific applications for Grid-environments. A toolbox designed and implemented in the frame of the DAMIEN project which closes some of the gaps and supports the end-user during the development of the application and its day-to-day usage in Grid-environments is then presented. © Springer-Verlag Berlin Heidelberg 2003.

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