ETDs

This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

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Modeling and control of flapping wing micro aerial vehicles

Description
Interest in Micro Aerial Vehicle (MAV) research has surged over the past decade. MAVs offer new capabilities for intelligence gathering, reconnaissance, site mapping, communications, search and rescue, etc. This thesis discusses key modeling and control aspects of flapping wing MAVs in hover. A three degree of freedom nonlinear model is…

Interest in Micro Aerial Vehicle (MAV) research has surged over the past decade. MAVs offer new capabilities for intelligence gathering, reconnaissance, site mapping, communications, search and rescue, etc. This thesis discusses key modeling and control aspects of flapping wing MAVs in hover. A three degree of freedom nonlinear model is used to describe the flapping wing vehicle. Averaging theory is used to obtain a nonlinear average model. The equilibrium of this model is then analyzed. A linear model is then obtained to describe the vehicle near hover. LQR is used to as the main control system design methodology. It is used, together with a nonlinear parameter optimization algorithm, to design a family multivariable control system for the MAV. Critical performance trade-offs are illuminated. Properties at both the plant output and input are examined. Very specific rules of thumb are given for control system design. The conservatism of the rules are also discussed. Issues addressed include

What should the control system bandwidth be vis--vis the flapping frequency (so that averaging the nonlinear system is valid)?

When is first order averaging sufficient? When is higher order averaging necessary?

When can wing mass be neglected and when does wing mass become critical to model?

This includes how and when the rules given can be tightened; i.e. made less conservative.
ContributorsBiswal, Shiba (Author) / Rodriguez, Armando (Thesis advisor) / Mignolet, Marc (Thesis advisor) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2015
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Image Processing Techniques for Object Sorting by a Two Degree of Freedom Robotic Manipulator: A Comparative Computer Simulation Study

Description
Object sorting is a very common application especially in the industry setting, but this is a labor intensive and time consuming process and it proves to be challenging if done manually. Thanks to the rapid development in technology now almost all these object sorting tasks are partially or completely automated.…

Object sorting is a very common application especially in the industry setting, but this is a labor intensive and time consuming process and it proves to be challenging if done manually. Thanks to the rapid development in technology now almost all these object sorting tasks are partially or completely automated. Image processing techniques are essential for the full operation of such a pick and place robot as it is responsible for perceiving the environment and to correctly identify ,classify and localize the different objects in it. In order for the robots to perform accurate object sorting with efficiency and stability this thesis discusses how different Deep learning based perception techniques can be used. In the era of Artificial Intelligence this sorting problem can be done more efficiently than the existing techniques. This thesis presents different image processing techniques and algorithms that can be used to perform object sorting efficiently. A comparison between three different deep learning based techniques is presented and their pros and cons are discussed. Furthermore this thesis also presents a comprehensive study about the kinematics and the dynamics involved in a 2 Degree of Freedom Robotic Manipulator .
ContributorsRanganathan, Pavithra (Author) / Rodriguez, Armando (Thesis advisor) / Si, Jennie (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2021