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Operations Research, Systems Engineering and Industrial Engineering Commons™
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- Closed Loop Systems (2)
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- <p>Teams in the workplace<br />Total quality management<br />Organizational effectiveness</p> (1)
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- Adaptive Force Balancing Control (1)
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Articles 1 - 11 of 11
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Feedback Linearization Based Power System Stabilizer Design With Control Limits, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Jagannathan Sarangapani
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 …
Successfully Blending Distance Students Into The On-Campus Classroom, Susan L. Murray, David Lee Enke, Sreeram Ramakrishnan
Successfully Blending Distance Students Into The On-Campus Classroom, Susan L. Murray, David Lee Enke, Sreeram Ramakrishnan
Engineering Management and Systems Engineering Faculty Research & Creative Works
As universities are increasingly embracing distance education technology, it is useful to examine the challenges and opportunities of technology in the classroom. This is especially true when the course contains on-campus local students in addition to students learning at a distance. A significant challenge commonly faced is how to remain flexible in presenting course materials while still having notes and other handouts in electronic format available before the lecture. Other challenges include creating and using lecture material that can be viewed at low resolution and low bandwidth, and getting distance students to interact with the instructor, on-campus students, and fellow …
Forecasting Series-Based Stock Price Data Using Direct Reinforcement Learning, H. Li, Cihan H. Dagli, David Lee Enke
Forecasting Series-Based Stock Price Data Using Direct Reinforcement Learning, H. Li, Cihan H. Dagli, David Lee Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
A significant amount of work has been done in the area of price series forecasting using soft computing techniques, most of which are based upon supervised learning. Unfortunately, there has been evidence that such models suffer from fundamental drawbacks. Given that the short-term performance of the financial forecasting architecture can be immediately measured, it is possible to integrate reinforcement learning into such applications. In this paper, we present the novel hybrid view for a financial series and critic adaptation stock price forecasting architecture using direct reinforcement. A new utility function called policies-matching ratio is also proposed. The need for the …
Cost Allocation For Transmission Investment Using Agent-Based Game Theory, Jakapun Mepokee, David Lee Enke, Badrul H. Chowdhury
Cost Allocation For Transmission Investment Using Agent-Based Game Theory, Jakapun Mepokee, David Lee Enke, Badrul H. Chowdhury
Engineering Management and Systems Engineering Faculty Research & Creative Works
Due to electrical power restructuring, a dramatic change has been made to the generation and transmission sectors of the power industry. Rules and legislation are continuously changing. To promote more competition, transmission has to be expanded or upgraded to remove congestion and market power. The cost allocation of new investment in transmission has to be recalculated. The socialization methods of the past have been shown to be unfair to some market and network participants. The decentralization of cost allocation must be considered. The proposed paper provides a comparison between traditional cost allocation methods and a new cost allocation method based …
Neural Network Controller For Manipulation Of Micro-Scale Objects, Vijayakumar Janardhan, Pingan He, Jagannathan Sarangapani
Neural Network Controller For Manipulation Of Micro-Scale Objects, Vijayakumar Janardhan, Pingan He, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement learning-based neural network (RLNN) controller is presented for the manipulation and handling of micro-scale objects in a microelectromechanical system (MEMS). In MEMS, adhesive, surface tension, friction and van der Waals forces are dominant. Moreover, these forces are typically unknown. The RLNN controller consists of an action NN for compensating the unkoown system dynamics, and a critic NN to tune the weights of the action NN. Using the Lyapunov approach, the uniformly ultimate houndedness (UUB) of the closed-loop tracking error and weight estimates are shown by using a novel weight updates. Simulation results are presented to substantiate the …
Discerning Attributes Which Stimulate Performance In Quality Improvement Teams, Dwan Lamar Prude
Discerning Attributes Which Stimulate Performance In Quality Improvement Teams, Dwan Lamar Prude
Masters Theses
"Total quality management (TQM) can be summed up as people and the way they work. One key element of the philosophies of TQM is the heavy emphasis on utilizing quality improvement teams (QITs) and quality tools to effectively create high performance organizations. Specifically, this investigation asks the following questions: 1) What are the key attributes that contribute to performance in QITs? 2) What is the relationship between team communication and QIT performance? 3) What is the relationship between the number of quality tools utilized in a team and QIT performance? Participants for this study were 101 students from the University …
A Distributed Power Control Mac Protocol For Wireless Ad-Hoc Networks., Maciej Jan Zawodniok, Jagannathan Sarangapani
A Distributed Power Control Mac Protocol For Wireless Ad-Hoc Networks., Maciej Jan Zawodniok, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A novel distributed power control (DPC)⋅ scheme and a MAC protocol for wireless ad hoc networks in the presence of radio channel uncertainties such as path loss, Shadowing and Rayleigh fading is presented. The DPC quickly estimates the time-varying nature of the channel and uses the information to select a suitable transmitter power value in order to maintain a target Signal-to-Interference ratio (SIR) at the receiver. The standard assumption of a constant interference during a link's power update used in other works is relaxed. The performance of the proposed DPC is demonstrated analytically. The power used for all RTS-CTS-DATA-ACK frames …
Adaptive Critic Neural Network-Based Object Grasping Control Using A Three-Finger Gripper, Gustavo Galan, Jagannathan Sarangapani
Adaptive Critic Neural Network-Based Object Grasping Control Using A Three-Finger Gripper, Gustavo Galan, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
Grasping of objects has been a challenging task for robots. The complex grasping task can be defined as object contact control and manipulation subtasks. In this paper, object contact control subtask is defined as the ability to follow a trajectory accurately by the fingers of a gripper. The object manipulation subtask is defined in terms of maintaining a predefined applied force by the fingers on the object. A sophisticated controller is necessary since the process of grasping an object without a priori knowledge of the object's size, texture, softness, gripper, and contact dynamics is rather difficult. Moreover, the object has …
Discrete-Time Neural Network Output Feedback Control Of Nonlinear Systems In Non-Strict Feedback Form, Pingan He, Jagannathan Sarangapani
Discrete-Time Neural Network Output Feedback Control Of Nonlinear Systems In Non-Strict Feedback Form, Pingan He, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
An adaptive neural network (NN)-based output feedback controller is proposed to deliver a desired tracking performance for a class of discrete-time nonlinear systems, which is represented in non-strict feedback form. The NN backstepping approach is utilized to design the adaptive output feedback controller consisting of: 1) a NN observer to estimate the system states with the input-output data, and 2) two NNs to generate the virtual and actual control inputs, respectively. The non-causal problem in the discrete-time backstepping design is avoided by using the universal NN approximator. The persistence excitation (PE) condition is relaxed both in the NN observer and …
Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow
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.
Adaptive Force-Balancing Control Of Mems Gyroscope With Actuator Limits, Mohammed Hameed, Jagannathan Sarangapani
Adaptive Force-Balancing Control Of Mems Gyroscope With Actuator Limits, Mohammed Hameed, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
This work presents an adaptive force-balancing control (AFBC) scheme with actuator limits for a MEMS Z-axis gyroscope. The purpose of the adaptive force-balancing control is to identify major fabrication imperfections so that they are properly compensated unlike the case of conventional force-balancing controlled gyroscope. The proposed AFBC scheme controls the vibratory modes of the proof mass while ensuring that the control input satisfies the magnitude constraints and the performance of the gyroscope is enhanced in the presence of fabrication uncertainties. Consequently, commonly reported problems of MEMS gyroscope such as quadrature compensation, drive and sense axes frequency tuning are not needed …