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Articles 571 - 600 of 692

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

Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier Jul 2007

Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, 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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Online Reinforcement Learning-Based Neural Network Controller Design For Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani Jul 2007

Online Reinforcement Learning-Based Neural Network Controller Design For Affine Nonlinear Discrete-Time Systems, 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 general multi-input and multi- output affine unknown nonlinear discrete-time systems in the presence of bounded disturbances. Adaptive critic designs consist of two entities, an action network that produces optimal solution 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 and the action network is adapted simultaneously based on the information from the critic. In our online learning method, one NN is designated as the …

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Selecting Electricity Generation Sources In Remote Locations, Kelly E. Kwan Mar 2007

Selecting Electricity Generation Sources In Remote Locations, Kelly E. Kwan

Theses and Dissertations

The purpose of this research was to investigate the impact of using a decision analysis technique for the selection of an electrical generation system for remote locations. Specifically, this thesis sought to answer five research questions addressing the types of energy sources used in remote locations, the decision-making processes used to identify these sources, the types of constraints incorporated in such a process, other valued factors, and their level of importance in relation to each other. The research questions were answered through a comprehensive literature review and the 10-Step Value-Focused Thinking Process on a specific case study in the National …

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Automatic Target Recognition User Interface Tool, David A. Kerns Mar 2007

Automatic Target Recognition User Interface Tool, David A. Kerns

Theses and Dissertations

A computer tool to aid in selecting the best Automatic Target Recognition (ATR) algorithm is developed. The program considers many quantifiers, accepts user-defined parameters, allows for changes in the operational environment and presents results in a meaningful way. It is written for Microsoft Excel. An ATR algorithm assigns a class label to a recognized target. General designations can include "Friend" and "Foe." The error of designating "Friend" as "Foe" as well as "Foe" as "Friend" comes with a high cost. Studying each algorithm's error can minimize this cost. Receiver Operating Characteristic (ROC) curves provide only information on the probabilities given …

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Adaptive Neural Network Based Stabilizing Controller Design For Single Machine Infinite Bus Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani, Mariesa Crow Jan 2007

Adaptive Neural Network Based Stabilizing Controller Design For Single Machine Infinite Bus Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani, Mariesa Crow

Engineering Management and Systems Engineering Faculty Research & Creative Works

Power system stabilizers are widely used to generate supplementary control signals for the excitation system in order to damp out the low frequency oscillations. In power system control literature, the performances of the proposed controllers were mostly demonstrated using simulation results without any rigorous stability analysis. This paper proposes a stabilizing neural network (NN) controller based on a sixth order single machine infinite bus power system model. The NN is used to approximate the complex nonlinear dynamics of power system. Unlike the other indirect adaptive NN control schemes, there is no offline training process and the NN can be directly …

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Spatial Diversity In Signal Strength Based Wlan Location Determination Systems, Anil Ramachandran, Jagannathan Sarangapani Jan 2007

Spatial Diversity In Signal Strength Based Wlan Location Determination Systems, Anil Ramachandran, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Literature indicates that spatial diversity can be utilized to compensate channel uncertainties such as multipath fading. Therefore, in this paper, spatial diversity is exploited for locating stationary and mobile objects in the indoor environment. First, space diversity technique is introduced for small scale motion and temporal variation compensation of received signal strength and it is demonstrated analytically that it enhances location accuracy. Small scale motion refers to movements of the transmitter and/or the receiver of the order of sub-wavelengths while temporal effects refer to environmental variations with time. A novel metric is introduced for selection combining in order to improve …

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An Online Approximator-Based Fault Detection Framework For Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani Jan 2007

An Online Approximator-Based Fault Detection Framework For Nonlinear Discrete-Time Systems, Balaje T. Thumati, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a fault detection scheme is developed for nonlinear discrete time systems. The changes in the system dynamics due to incipient failures are modeled as a nonlinear function of state and input variables while the time profile of the failures is assumed to be exponentially developing. The fault is detected by monitoring the system and is approximated by using online approximators. A stable adaptation law in discrete-time is developed in order to characterize the faults. The robustness of the diagnosis scheme is shown by extensive mathematical analysis and simulation results.

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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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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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Multi-Phase Flow Analysis In Oil And Gas Engineering Systems And Its Modelling, Orlando F. Ayala, Luis F. Ayala, Orlando M. Ayala Jan 2007

Multi-Phase Flow Analysis In Oil And Gas Engineering Systems And Its Modelling, Orlando F. Ayala, Luis F. Ayala, Orlando M. Ayala

Engineering Technology Faculty Publications

[Introduction] Two-phase flow is very common in industrial processes and its applications were already in use in ages as remote as the era of Archimedes. At the present time, many industrial processes rely on multi-phase phenomena for the transport of energy and mass or for material processing. During the last century, the nuclear, chemical and petroleum industries propelled intense research activity in the area. Their efforts have been aimed at the demystification of the mechanisms taking place during this complex flow situation.

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An Intervention Framework Based On A Complementary Theory Of Organizational Decline, George S. Mwaluko Dec 2006

An Intervention Framework Based On A Complementary Theory Of Organizational Decline, George S. Mwaluko

Tanzania Journal of Engineering and Technology (TJET)

This paper has developed an intervention framework based a complementary theory Of Organization decline. Any management intervention effort is normally based on a certain theory of organizational decline i.e. a theory that explains the causes for failure of organizations. Four major theories Of Organisational decline were identified in the literature, reviewed and integrated into one, presumably more superior, theory of organisational decline. They included the natural selection theory, the resourc+based theory, the theory Of misperception of feed!mck and the contingency theory. The new theory was then used to guide the design of an intervention framework. The framework utas then used …

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Towards Effective Online Learning Implementation In Tanzanian Higher Learning Institutions: Obstacles, Challenges And Opportunities, M Victor Dec 2006

Towards Effective Online Learning Implementation In Tanzanian Higher Learning Institutions: Obstacles, Challenges And Opportunities, M Victor

Tanzania Journal of Engineering and Technology (TJET)

This paper identifies and discusses several influential factors as well as opportunities, associated with effective- online learning implementation in Tanzanian Higher Learning Institutions (THUs). Fourteen (14) THUs were surveyed, using face-to-face interviews in focus groups. The groups included Lecturers, Heads of ICT Departments, ICT Technical Personnel as well as Admi/:listrative Staff. Results indicate that mostly, problems with effective online implementation in THUs are centred on a severe scarcity of online resources and tools and that the main challenges lie in going beyond the process of integrating technology with their teaching curricular, so that training of both teaching and supporting staffs …

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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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Order And Disorder, Entropy In Math, Science, Nature And The Arts, Sol Neeman Ph.D., Arie Maharshak Jul 2006

Order And Disorder, Entropy In Math, Science, Nature And The Arts, Sol Neeman Ph.D., Arie Maharshak

Engineering Studies Faculty Publications and Creative Works

Often, science and engineering students have difficult time in viewing certain concepts in their holistic form. An example for such a concept is the concept of Entropy. Although it originated from the field of thermodynamics, the relation between order and disorder is a profound one and manifests itself in various fields, sometimes unrelated, such as math and science, nature and the arts. In the discipline of physics, the amount of disorder in a system has been quantified by the concept of Entropy. In the area of information theory it provides a quantitative measure of the amount of compression that may …

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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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Socio-Economic Impacts Of Computer Viruses In Tanzania, M Victor Jun 2006

Socio-Economic Impacts Of Computer Viruses In Tanzania, M Victor

Tanzania Journal of Engineering and Technology (TJET)

This paper reports on a research project conducted with an objective of identifying and assessing various approaches used by different computer users (Management, System Administrators and end users) in Tanzania to combat computer viruses (CVs), and to assess users' awareness level on CVs. Specifically, the study aimed at assessing the awareness level on CVs to the Tanzanian business community; analyze the socio -economic impact caused by CVs in Tanzania and; assess existing methods, capacity and limitations on controlling CVs in Tanzania. Data was collected using both questionnaires and interview from financial institutions such as NBC and BOT, and telecommunications sector …

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Combining Quality Of Service And Topology Control In Directional Hybrid Wireless Networks, Michael C. Erwin Mar 2006

Combining Quality Of Service And Topology Control In Directional Hybrid Wireless Networks, Michael C. Erwin

Theses and Dissertations

Recent advancements in information and communications technology are changing the information environment in both quantitative and qualitative measures. The developments in directional wireless capabilities necessitate the ability to model these new capabilities, especially in dynamic environments typical of military combat operations. This thesis establishes a foundation for the definition and consideration of the unique network characteristics and requirements introduced by this novel instance of the Network Design Problem (NDP). Developed are a Mixed-Integer Linear Program (MILP) formulation and two heuristic strategies for solving the NDP. A third solution strategy using the MILP formulation with a degree-constrained Minimum Spanning Tree starting …

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Patterns In Team Communication During A Simulation Game, David M. Baca, Ray Luechtefeld, Steve Eugene Watkins Jan 2006

Patterns In Team Communication During A Simulation Game, David M. Baca, Ray Luechtefeld, Steve Eugene Watkins

Engineering Management and Systems Engineering Faculty Research & Creative Works

The development of communication skills is a necessary preparation for effective engineering teamwork. Argyris' "Theory of Action" provides a framework for understanding patterns in team dialogue. Students can benefit from an awareness of these patterns. The theory highlights the detection and correction of errors by sharing information during group collaboration and interactions. Quality decision-making can be enhanced when members of a team develop high degrees of openness and interdependence. Quality decision-making can be diminished when members of a team regulate the information shared within the team. This work analyzes team interactions from simulation games used in an interdisciplinary engineering course …

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Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He Jan 2006

Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He

Electrical and Computer Engineering Faculty Research & Creative Works

Spark ignition (SI) engines running at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle dispersion of heat release even though such operation can significantly reduce NOx emissions and improve fuel efficiency by as much as 5-10%. A suite of neural network (NN) controller without and with reinforcement learning employing output feedback has shown ability to reduce the nonlinear cyclic dispersion observed under lean operating conditions. The neural network controllers consists of three NN: a) A NN observer to estimate the states of the engine such as total fuel and air; b) a second NN for generating virtual input; …

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Adaptive And Probabilistic Power Control Algorithms For Dense Rfid Reader Network, Kainan Cha, Anil Ramachandran, Jagannathan Sarangapani Jan 2006

Adaptive And Probabilistic Power Control Algorithms For Dense Rfid Reader Network, Kainan Cha, Anil Ramachandran, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In radio frequency identification (RFID) systems, the detection range and read rates may suffer from interferences between high power devices such as readers. In dense networks, this problem grows severely and degrades system performance. In this paper, we investigate feasible power control schemes to ensure overall coverage area of the system while maintaining a desired data rate. The power control should dynamically adjust the output power of a RFID reader by adapting to the noise level seen during tag reading and acceptable signal-to-noise ratio (SNR). We present a novel distributed adaptive power control (DAPC) and probabilistic power control (PPC) as …

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Neuro Control Of Nonlinear Discrete Time Systems With Deadzone And Input Constraints, Pingan He, Wenzhi Gao, Jagannathan Sarangapani Jan 2006

Neuro Control Of Nonlinear Discrete Time Systems With Deadzone And Input Constraints, Pingan He, Wenzhi Gao, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A neural network (NN) controller in discrete time is designed to deliver a desired tracking performance for a class of uncertain nonlinear systems with unknown deadzones and magnitude constraints on the input. The NN controller consists of two NNs: the first NN for compensating the unknown deadzones; and the second NN for compensating the uncertain nonlinear system dynamics. The magnitude constraints on the input are modeled as saturation nonlinearities and they are dealt with in the Lyapunov-based controller design. The uniformly ultimate boundedness (UUB) of the closed-loop tracking errors and the neural network weights estimation errors is demonstrated via Lyapunov …

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Decentralized Power Control With Implementation For Rfid Networks, Kainan Cha, Anil Ramachandran, David Pommerenke, Jagannathan Sarangapani Jan 2006

Decentralized Power Control With Implementation For Rfid Networks, Kainan Cha, Anil Ramachandran, David Pommerenke, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In radio frequency identification (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. In this paper, we investigate a suite of feasible power control schemes to ensure overall coverage area of the system while maintaining a desired read rate. The power control scheme and MAC protocol dynamically adjusts the RFID reader power output in response to the interference level seen locally during tag reading for an acceptable signal-to-noise ratio (SNR). We present novel distributed adaptive power control (DAPC) and probabilistic …

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Development And Implementation Of Optimized Energy-Delay Sub-Network Routing Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda Jan 2006

Development And Implementation Of Optimized Energy-Delay Sub-Network Routing Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda

Electrical and Computer Engineering Faculty Research & Creative Works

The development and implementation of the optimized energy-delay sub-network routing (OEDSR) protocol for wireless sensor networks (WSN) is presented. This ondemand routing protocol minimizes a novel link cost factor which is defined using available energy, end-to-end (E2E) delay and distance from a node to the base station (BS), along with clustering, to effectively route information to the BS. Initially, the nodes are either in idle or sleep mode, but once an event is detected, the nodes near the event become active and start forming sub-networks. Formation of the inactive network into a sub-network saves energy because only a portion of …

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Distributed Power Control For Cellular Networks In The Presence Of Channel Uncertainties, Maciej Jan Zawodniok, Q. Shang, Jagannathan Sarangapani Jan 2006

Distributed Power Control For Cellular Networks In The Presence Of Channel Uncertainties, Maciej Jan Zawodniok, Q. Shang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel distributed power control (DPC) scheme for cellular network in the presence of radio channel uncertainties such as path loss, shadowing, and Rayleigh fading is presented. Since these uncertainties can attenuate the received signal strength and can cause variations in the received Signal-to-Interference ratio (SIR), a new DPC scheme, which can estimate the slowly varying channel uncertainty, is proposed so that a target SIR at the receiver can be maintained. Further, the standard assumption of a constant interference during a link's power update used in other works in the literature is relaxed. A CDMA-based cellular network …

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