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Khalili, MohsenDistributed Adaptive Fault-Tolerant Control of Nonlinear Uncertain Multi-Agent Systems
Doctor of Philosophy (PhD), Wright State University, 2017, Engineering PhD
The research on distributed multi-agent systems has received increasing attention due to its broad applications in numerous areas, such as unmanned ground and aerial vehicles, smart grid, sensor networks, etc. Since such distributed multi-agent systems need to operate reliably at all time, despite the possible occurrence of faulty behaviors in some agents, the development of fault-tolerant control schemes is a crucial step in achieving reliable and safe operations. The objective of this research is to develop a distributed adaptive fault-tolerant control (FTC) scheme for nonlinear uncertain multi-agent systems under intercommunication graphs with asymmetric weights. Under suitable assumptions, the closed-loop system's stability and leader-follower cooperative tracking properties are rigorously established. First, a distributed adaptive fault-tolerant control method for nonlinear uncertain first-order multi-agent systems is developed. Second, this distributed FTC method is extended to nonlinear uncertain second-order multi-agent systems. Next, adaptive-approximation-based FTC algorithms are developed for two cases of high-order multi-agent systems, i.e., with full-state measurement and with only limited output measurement, respectively. Finally, the distributed adaptive fault-tolerant formation tracking algorithms for first-order multi-agent systems are implemented and demonstrated using Wright State's real-time indoor autonomous robots test environment. The experimental formation tracking results illustrate the effectiveness of the proposed methods.

Committee:

Xiaodong Zhang, Ph.D. (Advisor); Kuldip Rattan, Ph.D. (Committee Member); Pradeep Misra, Ph.D. (Committee Member); Yongcan Cao, Ph.D. (Committee Member); Raul Ordonez, Ph.D. (Committee Member); Mark Mears, Ph.D. (Committee Member)

Subjects:

Electrical Engineering; Engineering

Keywords:

Fault-Tolerant Control; Adaptive Control; Multi-Agent Systems; Nonlinear Uncertain Systems; Formation Control; Learning Systems; Cooperative Tracking; Leader-Follower Consensus; Asymmetric Communication Graphs; Fault Diagnosis; Mobile Robots

SYED, ANEESCOLLISON PREDICTION AND AVOIDANCE OF SATELLITES IN FORMATION
MS, University of Cincinnati, 2004, Engineering : Mechanical Engineering
Satellites flying in formation has been the focus of current research. Sometimes,there are issues with the amount of information available about the satellites. Due to hardware limitations, full measurements of relative positions and velocities of the spacecraft may not be available. In the long-term, the only information available might be the inter-satellite ranges between the satellites. The first part of the present work aims at the reconstruction of the trajectory of a satellite from this limited information, i.e., the time history of inter-satellite range. The present work deals with the case of three satellites in formation. One satellite is at the reference in a near circular orbit and the other two satellites trace Hill’s orbits relative to the reference. The geometry and phasing of one satellite is assumed to be known and the trajectory parameters of the other satellite relative to the reference are computed. Due to atmospheric drag there is a possibility that one of the satellites may drift and slip out of the formation. This may lead to a collision between the two satellites which might damage any appendages on the spacecraft like the antennas. The objective of the second part of the thesis is to devise a strategy to avoid the collision. The solution from the first part will be used to predict a possible collision in the future and a suitable thrusting technique will be applied to avoid the collision. The only collision scenario considered, in the present work, is 'tangential orbits'.

Committee:

Dr. David Thompson (Advisor)

Keywords:

satellites; satellite formations; formation control; orbital mechanics

Gazi, VeyselStability Analysis of Swarms
Doctor of Philosophy, The Ohio State University, 2002, Electrical Engineering
Swarming, or aggregations of organisms in groups, can be found in nature in many organisms ranging from simple bacteria to mammals. Such behavior can result from several different mechanisms. For example, individuals may respond directly to local physical cues such as concentration of nutrients or distribution of some chemicals as seen in some bacteria and social insects, or they may respond directly to other individuals as seen in fish, birds, and herds of mammals. In this dissertation, we consider models for aggregating and social foraging swarms and perform rigorous stability analysis of emerging collective behavior. Moreover, we consider formation control of a general class of multi-agent systems in the framework of nonlinear output regulation problem with application on formation control of mobile robots. First, an individual-based continuous time model for swarm aggregation in an n-dimensional space is identified and its stability properties are analyzed. The motion of each individual is determined by two factors: (i) attraction to the other individuals on long distances and (ii) repulsion from the other individuals on short distances. It is shown that the individuals (autonomous agents or biological creatures) will form a cohesive swarm in a finite time. Moreover, explicit bounds on the swarm size and time of convergence are derived. Then, the results are generalized to a more general class of attraction/repulsion functions and extended to handle formation stabilization and uniform swarm density. After that, we consider social foraging swarms. We assume that the swarm is moving in an environment with an "attractant/repellent" profile (i.e., a profile of nutrients or toxic substances) which also affects the motion of each individual by an attraction to the more favorable or nutrient rich regions (or repulsion from the unfavorable or toxic regions) of the profile. The stability properties of the collective behavior of the swarm for different profiles are studied and conditions for collective convergence to more favorable regions are provided. Then, we use the ideas for modeling and analyzing the behavior of honey bee clusters and in-transit swarms, a phenomena seen during the reproduction of the bees. After that, we consider one-dimensional asynchronous swarms with time delays. We prove that, despite the asynchronism and time delays in the motion of the individuals, the swarm will converge to a comfortable position with comfortable intermember spacing. Finally, we consider formation control of a multi-agent system with general nonlinear dynamics. It is assumed that the formation is required to follow a virtual leader whose dynamics are generated by an autonomous neutrally stable system. We develop a decentralized control strategy based on the nonlinear output regulation (servomechanism) theory. We illustrate the procedure with application to formation control of mobile robots.

Committee:

Kevin Passino (Advisor)

Keywords:

swarms; stability analysis; multi-agent systems; formation control