Operations Research, Systems Engineering and Industrial Engineering Commons^™

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 …

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 …

Leadership In Student Distance Education Teams, Leroy Cox, Susan L. Murray, David Spurlock

Engineering Management and Systems Engineering Faculty Research & Creative Works

Interactive video technology has become a widely used medium for education. A prominent implementation of this technology, interactive distance learning, involves groups of students at local and remote sites connected by audio and video teleconferencing. This approach has made the task of delivering vital undergraduate and graduate engineering courses to distributed audiences much easier. As this approach has permeated more curricula, distance education instructors have increasingly assigned projects that require distance learners to work together as an element of the final course grade. This trend presents an interesting opportunity for researchers to understand the nature of interactions among course participants …

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 …

Applying The Mahalanobis-Taguchi System To Vehicle Handling, Kioumars Paryani, Elizabeth A. Cudney, K. M. Ragsdell

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Mahalanobis-Taguchi system (MTS) is a diagnosis and forecasting method using multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and patterns that can be identified and analyzed with respect to a base or reference group. The MTS is of interest because of its reported accuracy in forecasting using small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set …

A Methodology For Deriving System Requirements Using Agent Based System Modeling, Karthik Gopalakrishnan, Sreeram Ramakrishnan, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper, we duscuss a method to derive the requirements for developing an Industrial Automation and Constrol System (IACS). An IACS has software components and associated hardware, which together implement the required monitoring, supervision and control of operations an a production plant. The requirements of such a system are multi-dimensional and may require multiple layers of abstraction. For this domain, we propose an agent-based modeling adopting an agent-based modeling approach is the implicit flexibility afforded by agents and the negotiation techniques that can be implemented to streamline the change management process associated with requirements modeling and analysis. This paper …

A Simulation Framework For Real-Time Management And Control Of Inventory Routing Decisions, Shrikant Jarugumilli, Sreeram Ramakrishnan, Scott Erwin Grasman

Engineering Management and Systems Engineering Faculty Research & Creative Works

We consider a logistics network where a single warehouse distributes a single item to multiple retailers. Retailers in the network participate in a Vendor Managed Inventory (VMI) program with the warehouse, where the warehouse is responsible for tracking and replenishing the inventory at various retailer locations. The information update occurs every time a vehicle reaches a location and the decision on the delivery quantity and the next location to visit is made. For a small increase of locations in the network, the state space for the solution increases exponentially, making this problem NP-hard. Thus, we propose a solution methodology where …

Modeling Net-Centric System Of Systems Using The Dystems Modeling Language Sysml, Rao Madwaraj, Sreeram Ramakrishnan, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Understanding the operations of a large 'net-centric system-of-systems requires in-depth knowledge of the interfaces among the various systems, sub-systems and components. Architectural modeling can help in reducing the complexity involved in designing such large networked systems. An example of such a complex system is the Global Earth Observation System of Systems (GEOSS) - a system for monitoring and collecting information related to Earth's resources. This paper demonstrates the use of Systems Modeling Language (SysML), which supports specification, analysis, design, verification and validation of a broad range of complex systems, to model some aspects of the GEOSS. The paper discusses issues …

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 …

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 …

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 …

Evaluation Of The Effect Of Vehicle Performance On Consumer Satisfaction, Elizabeth A. Cudney

Doctoral Dissertations

"Value is the relationship of functionality or benefit to the cost of a product or service. Consumers appear to seek value, but not all consumers are alike in their needs and wants. Common characteristics that consumers desire in automobiles include a high level of value relative to the product's cost. Consumers measure vehicle performance in terms of twenty-three attributes such as roominess, ride, reliability, handling, brake pedal feel, visibility, interior noise, acceleration, etc. Problems arise when automakers try to translate these characteristics into vehicle performance specifications and capabilities.

Quality is an essential element for both the consumer and producer since …

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 …

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 …

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; …

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 …