Matching Items (4)
Filtering by
- Creators: Mechanical and Aerospace Engineering Program
- Resource Type: Text
Description
Modern measurement schemes for linear dynamical systems are typically designed so that different sensors can be scheduled to be used at each time step. To determine which sensors to use, various metrics have been suggested. One possible such metric is the observability of the system. Observability is a binary condition determining whether a finite number of measurements suffice to recover the initial state. However to employ observability for sensor scheduling, the binary definition needs to be expanded so that one can measure how observable a system is with a particular measurement scheme, i.e. one needs a metric of observability. Most methods utilizing an observability metric are about sensor selection and not for sensor scheduling. In this dissertation we present a new approach to utilize the observability for sensor scheduling by employing the condition number of the observability matrix as the metric and using column subset selection to create an algorithm to choose which sensors to use at each time step. To this end we use a rank revealing QR factorization algorithm to select sensors. Several numerical experiments are used to demonstrate the performance of the proposed scheme.
ContributorsIlkturk, Utku (Author) / Gelb, Anne (Thesis advisor) / Platte, Rodrigo (Thesis advisor) / Cochran, Douglas (Committee member) / Renaut, Rosemary (Committee member) / Armbruster, Dieter (Committee member) / Arizona State University (Publisher)
Created2015
Description
This study aims to showcase the results of a quadrotor model and the mathematical techniques used to arrive at the proposed design. Multicopters have made an explosive appearance in recent years by the controls engineering community because of their unique flight performance capabilities and potential for autonomy. The ultimate goal of this research is to design a robust control system that guides and tracks the quadrotor's trajectory, while responding to outside disturbances and obstacles that will realistically be encountered during flight. The first step is to accurately identify the physical system and attempt to replicate its behavior with a simulation that mimics the system's dynamics. This becomes quite a complex problem in itself because many realistic systems do not abide by simple, linear mathematical models, but rather nonlinear equations that are difficult to predict and are often numerically unstable. This paper explores the equations and assumptions used to create a model that attempts to match roll and pitch data collected from multiple test flights. This is done primarily in the frequency domain to match natural frequency locations, which can then be manipulated judiciously by altering certain parameters.
ContributorsDuensing, Jared Christopher (Author) / Takahashi, Timothy (Thesis director) / Garrett, Frederick (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
ContributorsGoodwin, Walter (Author) / Yong, Sze Zheng (Thesis director) / Grewal, Anoop (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-05
ContributorsGoodwin, Walter (Author) / Yong, Sze Zheng (Thesis director) / Grewal, Anoop (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-05