ASU Electronic Theses and Dissertations
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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- All Subjects: Data Analytics
- All Subjects: Nonlinear simulation
Description
Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly organized into the following two parts: I) spatio-temporal wind power analysis for wind generation forecast and integration, and II) data mining and information fusion of synchrophasor measurements toward secure power grids. Part I is centered around wind power generation forecast and integration. First, a spatio-temporal analysis approach for short-term wind farm generation forecasting is proposed. Specifically, using extensive measurement data from an actual wind farm, the probability distribution and the level crossing rate of wind farm generation are characterized using tools from graphical learning and time-series analysis. Built on these spatial and temporal characterizations, finite state Markov chain models are developed, and a point forecast of wind farm generation is derived using the Markov chains. Then, multi-timescale scheduling and dispatch with stochastic wind generation and opportunistic demand response is investigated. Part II focuses on incorporating the emerging synchrophasor technology into the security assessment and the post-disturbance fault diagnosis of power systems. First, a data-mining framework is developed for on-line dynamic security assessment by using adaptive ensemble decision tree learning of real-time synchrophasor measurements. Under this framework, novel on-line dynamic security assessment schemes are devised, aiming to handle various factors (including variations of operating conditions, forced system topology change, and loss of critical synchrophasor measurements) that can have significant impact on the performance of conventional data-mining based on-line DSA schemes. Then, in the context of post-disturbance analysis, fault detection and localization of line outage is investigated using a dependency graph approach. It is shown that a dependency graph for voltage phase angles can be built according to the interconnection structure of power system, and line outage events can be detected and localized through networked data fusion of the synchrophasor measurements collected from multiple locations of power grids. Along a more practical avenue, a decentralized networked data fusion scheme is proposed for efficient fault detection and localization.
ContributorsHe, Miao (Author) / Zhang, Junshan (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Hedman, Kory (Committee member) / Si, Jennie (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
Vertical take-off and landing (VTOL) systems have become a crucial component of aeronautical and commercial applications alike. Quadcopter systems are rather convenient to analyze and design controllers for, owing to symmetry in body dynamics. In this work, a quadcopter model at hover equilibrium is derived, using both high and low level control. The low level control system is designed to track reference Euler angles (roll, pitch and yaw) as shown in previous work [1],[2]. The high level control is designed to track reference X, Y, and Z axis states [3].
The objective of this paper is to model, design and simulate platooning (separation) control for a fleet of 6 quadcopter units, each comprising of high and low level control systems, using a leader-follower approach. The primary motivation of this research is to examine the ”accordion effect”, a phenomenon observed in leader-follower systems due to which positioning or spacing errors arise in follower vehicles due to sudden changes in lead vehicle velocity. It is proposed that the accordion effect occurs when lead vehicle information is not directly communicated with the rest of the
system [4][5]
.
In this paper, the effect of leader acceleration feedback is observed for the quadcopter platoon. This is performed by first designing a classical platoon controller for a nominal case, where communication within the system is purely ad-hoc (i.e from one quadcopter to it’s immediate successor in the fleet). Steady state separation/positioning errors for each member of the fleet are observed and documented during simulation. Following this analysis, lead vehicle acceleration is provided to the controller (as a feed forward term), to observe the extent of it’s effect on steady state separation, specifically along tight maneuvers. Thus the key contribution of this work is a controller that stabilizes a platoon of quadcopters in the presence of the accordion effect, when employing a leader-follower approach. The modeling shown in this paper builds on previous research to design a low costquadcopter platform, the Mark 3 copter [1]. Prior to each simulation, model nonlinearities and hardware constants are measured or derived from the Mark 3 model, in an effort to observe the working of the system in the presence of realistic hardware constraints. The system is designed in compliance with Robot Operating System (ROS) and the Micro Air Vehicle Link (MAVLINK) communication protocol.
ContributorsSrinivasan, Anshuman (Author) / Rodriguez, Armando A. (Thesis advisor) / Si, Jennie (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2021