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Articles 601 - 630 of 709

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

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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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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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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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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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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Adaptive Distributed Fair Scheduling And Its Implementation In Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda Jan 2006

Adaptive Distributed Fair Scheduling And Its Implementation In Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda

Electrical and Computer Engineering Faculty Research & Creative Works

A novel adaptive and distributed fair scheduling (ADFS) scheme for wireless sensor networks is shown through hardware implementation. In contrast to simulation, hardware evaluation provides valuable feedback to protocol and hardware development process. The proposed protocol focuses on quality-of-service (QoS) issues to address flow prioritization. Thus, when nodes access a shared channel, the proposed ADFS allocates the channel bandwidth proportionally to the weight, or priority, of the packet flows. Moreover, ADFS allows for dynamic allocation of network resources with little added overhead. Weights are initially assigned using user specified QoS criteria. These weights are subsequently updated as a function of …

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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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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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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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Knowledge Representation, Organization, And Formalization For Simulation Modeling Of Discrete Manufacturing System, Jung Hung Ma Aug 2005

Knowledge Representation, Organization, And Formalization For Simulation Modeling Of Discrete Manufacturing System, Jung Hung Ma

All-Inclusive List of Electronic Theses and Dissertations

Simulation is an useful tool that helps managers making decision by designing models for real systems. It helps companies to study behaviors of real systems hy analyzing computer models and improve the systems based on the experiments' results. However, cross-domain knowledge requirement and lack of tools facilitate modeling are the main reasons that make industries hesitate to use simulation to assist making decision. This research is an attempt to develop robust knowledge representations for discrete manufacturing system and conceptual simulation model. A modeling methodology was proposed to utilize these knowledge representations (KRs) for developing conceptual simulation models from application domain …

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Study Of The Impact Of Quality Costs On Profitability: The Case Of Small And Medium Industries In Tanazania, B Kundi Jun 2005

Study Of The Impact Of Quality Costs On Profitability: The Case Of Small And Medium Industries In Tanazania, B Kundi

Tanzania Journal of Engineering and Technology (TJET)

No abstract provided.

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Reinforcement Learning-Based Output Feedback Control Of Nonlinear Systems With Input Constraints, Pingan He, Jagannathan Sarangapani Feb 2005

Reinforcement Learning-Based Output Feedback Control Of Nonlinear Systems With Input Constraints, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel neural network (NN) -based output feedback controller with magnitude constraints is designed to deliver a desired tracking performance for a class of multi-input-multi-output (MIMO) discrete-time strict feedback nonlinear systems. Reinforcement learning in discrete time is proposed for the output feedback controller, which uses three NN: 1) a NN observer to estimate the system states with the input-output data; 2) a critic NN to approximate certain strategic utility function; and 3) an action NN to minimize both the strategic utility function and the unknown dynamics estimation errors. The magnitude constraints are manifested as saturation nonlinearities in the output feedback …

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Work In Progress - Automated Discourse Interventions And Student Teaming, Ray Luechtefeld, Steve Eugene Watkins, Ralph E. Flori Feb 2005

Work In Progress - Automated Discourse Interventions And Student Teaming, Ray Luechtefeld, Steve Eugene Watkins, Ralph E. Flori

Engineering Management and Systems Engineering Faculty Research & Creative Works

The ability to successfully work in teams is a crucial part of an engineer's workplace success. Engineering education can be improved through a better understanding of how effective teamwork develops. A (patent pending) software tool that "listens" to team conversations and generates automatic interventions into team discourse can effectively mimic the actions of a skilled facilitator. Automated facilitation tools may help students improve their team skills by providing a simplified model for conversational interventions, which students can readily imitate. This paper describes this tool and presents preliminary findings from student reactions to the tool's use.

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Management Of Extremes In The Configuration Of Interoffice Telephone Switch & Priority Systems, C. Ariel Pinto Jan 2005

Management Of Extremes In The Configuration Of Interoffice Telephone Switch & Priority Systems, C. Ariel Pinto

Engineering Management & Systems Engineering Faculty Publications

This paper describes how to enable diverse enterprise customers for voice-data switch to achieve in configuration a balance among users, features, and perceived reliability subject to extremes of traffic. The analysis entailed the simulation of the voice-data switch with embedded priority system, generation of latency times for various configurations and transaction traffic rates, and the development of a framework and theoretical propositions for configuration of super-saturated systems. It was shown that the concept of tolerance levels defined in the risk of extreme events can be applied for embedded priority systems and was the basis for the application of the zone-configuration …

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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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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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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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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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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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