Investigation of Active Failure Detection Algorithms

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Title: Investigation of Active Failure Detection Algorithms
Author: Hannas, Benjamin L
Advisors: Dr. Stephen L. Campbell, Committee Chair
Dr. Mette S. Olufsen, Committee Member
Dr. Hien T. Tran, Committee Member
Abstract: This study analyzes two robust failure detection algorithms and applies the algorithms to three power system models. An optimal test signal to distinguish between a failure model and a normal model is calculated using the two algorithms. Advantages and disadvantages of each algorithm, Direct Optimization (DO) and Constrained Control (CC), are discussed. DO uses complex software (Sparse Optimal Control Software by The Boeing Corporation) to solve the necessary and boundary conditions of the optimization problem directly. CC utilizes free software (SciLab by Inria, Enpc.) to solve a two-point boundary value problem based on the necessary and boundary conditions of the optimization problem. Both algorithms yield similar signals, but DO is faster and more accurate yet requires expensive software. CC is not as robust, but can be run on free software and does not need as much fine tuning as the DO algorithm. Examples presented are two DC motor models and a linearized gas turbine model.
Date: 2006-02-28
Degree: MS
Discipline: Applied Mathematics
URI: http://www.lib.ncsu.edu/resolver/1840.16/2023


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