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Operations Research, Systems Engineering and Industrial Engineering Commons™

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2005

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Articles 271 - 276 of 276

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

Software Development Project Risk Management: A Literature Review, Kevin Macg. Adams, C. Ariel Pinto Jan 2005

Software Development Project Risk Management: A Literature Review, Kevin Macg. Adams, C. Ariel Pinto

Engineering Management & Systems Engineering Faculty Publications

The rapid and unprecedented growth in software has brought with it some of the most spectacular and costly project failures in modern history. How risk management is presented in the scholarly journals may give insight into the risk management methods and techniques in use on software development projects. This paper provides a glimpse into the risk management methods, methodologies and techniques available to those who are responsible for software development projects by conducting a non-experimental content analysis. The findings reveal that risk management has not received sufficient attention and does not appear to be widely accepted within the software engineering …

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Development Of A System Of Systems Engineering Method, Ji Hyon Mun, Morgan Henrie, Yaneth Correa, Charles Keating, Andres Sousa-Poza Jan 2005

Development Of A System Of Systems Engineering Method, Ji Hyon Mun, Morgan Henrie, Yaneth Correa, Charles Keating, Andres Sousa-Poza

Engineering Management & Systems Engineering Faculty Publications

Systems engineers have been facing challenges with the design and analysis of multiple complex systems. System of Systems Engineering has emerged to assist in this challenge with the systemic analysis, design, and transformation of complex metasystems. This paper outlines a proposed method to overcome these challenges, which is grounded in System of Systems Engineering principles and methodology. An overview of System of Systems Engineering will be provided for understanding of its significance and the attempt to complement Systems Engineering efforts in dealing with the aforementioned challenges. Finally, discussion on the proposed method, with respect to complex system analysis, is provided.

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Neural Network -Based Nearly Optimal Hamilton-Jacobi-Bellman Solution For Affine Nonlinear Discrete-Time Systems, Jagannathan Sarangapani, Zheng Chen Jan 2005

Neural Network -Based Nearly Optimal Hamilton-Jacobi-Bellman Solution For Affine Nonlinear Discrete-Time Systems, Jagannathan Sarangapani, Zheng Chen

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we consider the use of nonlinear networks towards obtaining nearly optimal solutions to the control of nonlinear discrete-time systems. The method is based on least-squares successive approximation solution of the Generalized Hamilton-Jacobi-Bellman (HJB) equation. Since successive approximation using the GHJB has not been applied for nonlinear discrete-time systems, the proposed recursive method solves the GHJB equation in discrete-time on a well-defined region of attraction. The definition of GHJB, Pre-Hamiltonian function, HJB equation and method of updating the control function for the affine nonlinear discrete time systems are proposed. A neural network is used to approximate the GHJB …

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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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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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