A Tight Lower Bound on the Controllability of Networks with Multiple Leaders

In this paper we study the controllability of networked systems with static network topologies using tools from algebraic graph theory. Each agent in the network acts in a decentralized fashion by updating its state in accordance with a nearest-neighbor averaging rule, known as the consensus dynamics. In order to control the system, external control inputs are injected into the so called leader nodes, and the influence is propagated throughout the network. Our main result is a tight topological lower bound on the rank of the controllability matrix for such systems with arbitrary network topologies and possibly multiple leaders

Image based visual servoing using algebraic curves applied to shape alignment

Visual servoing schemes generally employ various image features (points, lines, moments etc.) in their control formulation. This paper presents a novel method for using boundary information in visual servoing. Object boundaries are modeled by algebraic equations and decomposed as a unique sum of product of lines. We propose that these lines can be used to extract useful features for visual servoing purposes. In this paper, intersection of these lines are used as point features in visual servoing. Simulations are performed with a 6 DOF Puma 560 robot using Matlab Robotics Toolbox for the alignment of a free-form object. Also, experiments are realized with a 2 DOF SCARA direct drive robot. Both simulation and experimental results are quite promising and show potential of our new method

Motion estimation of planar curves and their alignment using visual servoing

Motion estimation and vision based control have been steadily improving research areas recently. Visual motion estimation is the determination of underlying motion parameters by using image data. Visual servoing on the other hand refers to the closed loop control of robotic systems using vision. Solving these problems with objects that have simple geometric features, such as points and lines is rather easy. However, these problems may imply certain challenges when we deal with curved objects that lack such simple features. This thesis proposes novel vision based estimation and control techniques that use object boundary information. Object boundaries are represented by planar algebraic curves. Decomposition of algebraic curves are used to extract features for motion estimation and visual servoing. Motion estimation algorithm uses the parameters of line factors resulting from the decomposition of the curve whereas visual servoing method employs the intersections of lines. Motion estimation algorithm is verified with several simulations and experiments. Visual servoing algorithm developed for the arbitrary alignment of a planar object is tested both with simulations on a 6 DOF Puma 560 robot and experiments on a 2 DOF SCARA robot. Results are quite promising

Decentralized graph processes for robust multi-agent networks

The objective of this thesis is to develop decentralized methods for building robust multi-agent networks through self-organization. Multi-agent networks appear in a large number of natural and engineered systems, including but not limited to, biological networks, social networks, communication systems, transportation systems, power grids, and robotic swarms. Networked systems typically consist of numerous components that interact with each other to achieve some collaborative tasks such as flocking, coverage optimization, load balancing, or distributed estimation, to name a few. Multi-agent networks are often modeled via interaction graphs, where the nodes represent the agents and the edges denote direct interactions between the corresponding agents. Interaction graphs play a significant role in the overall behavior and performance of multi-agent networks. There- fore, graph theoretic analysis of networked systems has received a considerable amount of attention within the last decade. In many applications, network components are likely to face various functional or structural disturbances including, but not limited to, component failures, noise, or malicious attacks. Hence, a desirable network property is robustness, which is the ability to perform reasonably well even when the network is subjected to such perturbations. In this thesis, robustness in multi-agent networks is pursued in two parts. The first part presents a decentralized graph reconfiguration scheme for formation of robust interaction graphs. Particularly, the proposed scheme transforms any interaction graph into a random regular graph, which is robust to the perturbations of their nodes/links. The second part presents a decentralized coverage control scheme for optimal protection of networks by some mobile security resources. As such, the proposed scheme drives a group of arbitrarily deployed resources to optimal locations on a network in a decentralized fashion.Ph.D

Resilient Control of Transportation Networks by Using Variable Speed Limits

© 2017 IEEE. We investigate the use of variable speed limits for resilient operation of transportation networks, which are modeled as dynamical flow networks under local routing decisions. In such systems, some external inflow is injected to the so-called origin nodes of the network. The total inflow arriving at each node is routed to its operational outgoing links based on their current densities of traffic. The density on each link has first-order dynamics driven by the difference of its incoming and outgoing flows. A link fails if it reaches its jam density. Such failures may propagate in the network and cause a systemic failure. We show that larger link capacities, that is, the maximum flows that can be sustained by the links, are not always better for preventing systemic failures under local routing. Accordingly, we propose the use of variable speed limits to operate the links below their capacities, when necessary, to compensate for the lack of global information and coordination in routing decisions. We show that systemic failures under feasible external inflows can always be averted through proper selection of speed limits if the routing decisions are sufficiently responsive to local congestion and the network is initially uncongested. This is an attractive feature as it provides a practical alternative to building more physical capacity or altering routing decisions that are determined by social behavior