Operations Research, Systems Engineering and Industrial Engineering Commons^™

A Systems Approach For Solving Inter-Policy Gaps In Dynamic Spectrum Access-Based Wireless Rural Broadband Networks, Pawel Kryszkiewicz, Casey I. Canfield, Shamsnaz Virani Bhada, Alexander M. Wyglinski

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper, we articulate the challenge of multiple intersecting policies for the realization of rural broadband networks employing dynamic spectrum access (DSA). Broadband connectivity has been identified as a critical component of economic development, especially during the COVID-19 pandemic, and rural communities have been significantly (and negatively) affected by the lack of this important resource. Although technologies exist that can deliver broadband connectivity, such as 4G LTE and 5G cellular networks, the challenges associated with efficiently deploying this infrastructure within a rural environment are multi-dimensional in terms of the different dependent policy decisions that need to be considered. To …

Reducing Kidney Discard With Artificial Intelligence Decision Support: The Need For A Transdisciplinary Systems Approach, Richard Threlkeld, Lirim Ashiku, Casey I. Canfield, Daniel Burton Shank, Mark A. Schnitzler, Krista L. Lentine, David A. Axelrod, Anil Choudary Reddy Battineni, Henry Randall, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Purpose of Review: A transdisciplinary systems approach to the design of an artificial intelligence (AI) decision support system can more effectively address the limitations of AI systems. By incorporating stakeholder input early in the process, the final product is more likely to improve decision-making and effectively reduce kidney discard.

Recent Findings: Kidney discard is a complex problem that will require increased coordination between transplant stakeholders. An AI decision support system has significant potential, but there are challenges associated with overfitting, poor explainability, and inadequate trust. A transdisciplinary approach provides a holistic perspective that incorporates expertise from engineering, social science, and …

Network-Centric Localization In Manets Based On Particle Swarm Optimization, Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy, Ann K. Miller, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes need to locate a target or surround it. Severe resource constraints in MANETs call for energy efficient target localization and collaborative navigation. Centralized control of MANET nodes is not an attractive solution due to its high network utilization that can result in congestions and delays. In nature, many colonies of biological species (such as a flock of birds) can achieve effective collaborative navigation without any centralized control. Particle swarm optimization (PSO), a popular swarm intelligence approach that models social dynamics of a biological swarm is …

Sr-2: A Hybrid Algorithm For The Capacitated Vehicle Routing Problem, Angel A. Juan, Javier Faulin, Josep Jorba, Barry Barrios, Scott Erwin Grasman

Engineering Management and Systems Engineering Faculty Research & Creative Works

During the last decades a lot of work has been devoted to develop algorithms that can provide near-optimal solutions for the capacitated vehicle routing problem (CVRP). Most of these algorithms are designed to minimize an objective function, subject to a set of constraints, which typically represents aprioristic costs. This approach provides adequate theoretical solutions, but they do not always fit real-life needs since there are some important costs and some routing constraints or desirable properties that cannot be easily modeled. In this paper, we present a new approach which combines the use of Monte Carlo simulation and parallel and grid …

Implementing An Architectural Framework To Define And Deliver Net-Centric Capability To Legacy Military Air Assets Operating Within A System Of Systems, Mark S. Anderson, S. M. Martin, Cihan H. Dagli, Ann K. Miller

Engineering Management and Systems Engineering Faculty Research & Creative Works

The United States Air Force (USAF) is implementing an integrated net-centric system of systems for airborne operations in support of the global war on terror (GWOT). The GWOT demands that a successful architecture framework transforms and delivers net-centric assets to the war-fighter in a timely manner. A critical component of this implementation is the transformation of legacy strategic air platforms into net-centric air power assets operating within a system of systems. The System Architectural (SA) framework, and the Department of Defense Architectural Framework (DoDAF) are ways of managing complexity and organizing information within a system of systems network. This paper …

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 …

An Evaluation Of Mahalanobis-Taguchi System And Neural Network For Multivariate Pattern Recognition, Jungeui Hong, Rajesh Jugulum, Kioumars Paryani, K. M. Ragsdell, Genichi Taguchi, Elizabeth A. Cudney

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis- Taguchi System and a neural-network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class.

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 …

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 …

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 …

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 …

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 …

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 …

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.

Evolving Neural Networks Applied To Predator-Evader Problem, Shivakumar Viswanathan, Ilker Ersoy, Filiz Bunyak, Cihan H. Dagli

Computer Science Faculty Research & Creative Works

The creation of strategies to meet abstract goals is an important behavior exhibited by natural organisms. A situation requiring the development of such strategies is the predator-evader problem. To study this problem, Khepera robots are chosen as the competing agents. Using computer simulations the evolution of the adaptive behavior is studied in a predator-evader interaction. A bilaterally symmetrical multilayer perceptron neural network architecture with evolvable weights is used to model the “brains” of the agents. Evolutionary programming is employed to evolve the predator for developing adaptive strategies to meet its goals. To study the effect of learning on evolution a …

A Transmission-Constrained Unit Commitment Method, Chung-Li Tseng, Chao-An Li, S. S. Oren, C. S. Cheng, A. J. Svoboda, R. B. Johnson

Engineering Management and Systems Engineering Faculty Research & Creative Works

The paper presents a transmission-constrained unit commitment method using a Lagrangian relaxation approach. The transmission constraints are modeled as linear constraints based on a DC power flow model. The transmission constraints, as well as the demand and spinning reserve constraints, are relaxed by attaching Lagrange multipliers. The authors take a new approach in the algorithmic scheme. A three-phase algorithm is devised including dual optimization, a feasibility phase and unit decommitment. A test problem involving more than 2500 transmission lines and 2200 buses is tested along with other test problems

A Robust Unit Commitment Algorithm For Hydro-Thermal Optimization, Chao-An Li, R. B. Johnson, A. J. Svoboda, Chung-Li Tseng, E. Hsu

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents a unit commitment algorithm which combines the Lagrangian relaxation (LR), sequential unit commitment (SUC), and optimal unit decommitment (UD) methods to solve a general hydro-thermal optimization (HTO) problem. We argue that this approach retains the advantages of the LR method while addressing the method''s observed weaknesses to improve overall algorithm performance and quality of solution. The proposed approach has been implemented in a version of PG&E''s HTO program, and test results are presented.

A Robust Unit Commitment Algorithm For Hydro-Thermal Optimization, Chao-An Li, Chung-Li Tseng, E. Hsu, R. B. Johnson, A. J. Svoboda

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents a unit commitment algorithm which combines the Lagrangian relaxation (LR), sequential unit commitment (SUC), and optimal unit decommitment (UD) methods to solve a general hydro-thermal optimization (HTO) problem. The authors argue that this approach retains the advantages of the LR method while addressing the method''s observed weaknesses to improve overall algorithm performance and quality of solution. The proposed approach has been implemented in a version of PG&E''s HTO program, and test results are presented.

Short-Term Resource Scheduling With Ramp Constraints [Power Generation Scheduling], Chung-Li Tseng, Chao-An Li, A. J. Svoboda, R. B. Johnson

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper describes a Lagrangian relaxation-based method to solve the short-term resource scheduling (STRS) problem with ramp constraints. Instead of discretizing the generation levels, the ramp rate constraints are relaxed with the system demand constraints using Lagrange multipliers. Three kinds of ramp constraints, startup, operating and shutdown ramp constraints are considered. The proposed method has been applied to solve the hydro-thermal generation scheduling problem at PG&E. An example alone with numerical results is also presented