In this paper, we discuss consensus problems for networks of dynamic agents with fixed and switching topologies. We analyze three cases: 1) directed networks with fixed topology; 2) directed networks with switching topology; and 3) undirected networks with communication time-delays and fixed topology. We introduce two consensus protocols for networks with and without time-delays and provide a convergence analysis in all three cases. We establish a direct connection between the algebraic connectivity (or Fiedler eigenvalue) of the network and the performance (or negotiation speed) of a linear consensus protocol. This required the generalization of the notion of algebraic connectivity of undirected graphs to digraphs. It turns out that balanced digraphs play a key role in addressing average-consensus problems. We introduce disagreement functions for convergence analysis of consensus protocols. A disagreement function is a Lyapunov function for the disagreement network dynamics. We proposed a simple disagreement function that is a common Lyapunov function for the disagreement dynamics of a directed network with switching topology. A distinctive feature of this work is to address consensus problems for networks with directed information flow. We provide analytical tools that rely on algebraic graph theory, matrix theory, and control theory. Simulations are provided that demonstrate the effectiveness of our theoretical results.

/pdf/consensus-problems-in-networks-of-agents-with-switching-25c3hqvtd8.pdf

Consensus problems in networks of agents with switching topology and time-delays

In this paper, we intend to formulate a new meta-heuristic algorithm, called Cuckoo Search (CS), for solving optimization problems. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Levy flight behaviour of some birds and fruit flies. We validate the proposed algorithm against test functions and then compare its performance with those of genetic algorithms and particle swarm optimization. Finally, we discuss the implication of the results and suggestion for further research.

Cuckoo Search via Lévy flights

http://masou-keshtkar.persiangig.com/document/sdarticle.pdf

GSA: A Gravitational Search Algorithm

In this paper, we present a theoretical framework for design and analysis of distributed flocking algorithms. Two cases of flocking in free-space and presence of multiple obstacles are considered. We present three flocking algorithms: two for free-flocking and one for constrained flocking. A comprehensive analysis of the first two algorithms is provided. We demonstrate the first algorithm embodies all three rules of Reynolds. This is a formal approach to extraction of interaction rules that lead to the emergence of collective behavior. We show that the first algorithm generically leads to regular fragmentation, whereas the second and third algorithms both lead to flocking. A systematic method is provided for construction of cost functions (or collective potentials) for flocking. These collective potentials penalize deviation from a class of lattice-shape objects called /spl alpha/-lattices. We use a multi-species framework for construction of collective potentials that consist of flock-members, or /spl alpha/-agents, and virtual agents associated with /spl alpha/-agents called /spl beta/- and /spl gamma/-agents. We show that migration of flocks can be performed using a peer-to-peer network of agents, i.e., "flocks need no leaders." A "universal" definition of flocking for particle systems with similarities to Lyapunov stability is given. Several simulation results are provided that demonstrate performing 2-D and 3-D flocking, split/rejoin maneuver, and squeezing maneuver for hundreds of agents using the proposed algorithms.

/pdf/flocking-for-multi-agent-dynamic-systems-algorithms-and-5efqu9aidp.pdf

Flocking for multi-agent dynamic systems: algorithms and theory

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

In this article we consider the formation control problem of a system of M agents with general nonlinear dynamics. We show that the problem of the agents moving in a formation along constant or periodic trajectories can be formulated as a nonlinear output regulation (servomechanism) problem and solved using known techniques. Then, we consider the example of formation control of agents with point mass dynamics and apply the procedure. Few illustrative numerical simulation examples are also provided.

Formation control of a multi-agent system using decentralized nonlinear servomechanism

In this article we develop a direct adaptive fuzzy control based methodology for formation control and target tracking in a class of multi-agent systems with nonlinear and uncertain dynamics. The agents are assumed to be able to measure only their relative position to the other agents and the target and high gain observers are applied to estimate the derivatives of the combined tracking and formation errors. Various formation maneuvers such as contraction/expansion, rotation, and reconfiguration of the formation are also considered. Bounding and sliding mode control terms are used to guarantee stability and robust performance. Simple numerical simulations are also provided to verify the effectiveness of the algorithm.

Adaptive formation control and target tracking in a class of multi-agent systems: Formation maneuvers

This article presents a novel algorithm for multiple odor source localization by a multi-robot system based on a virtual cancelation plume approach. The proposed method is based on rendering a previously declared odor source invisible to the robots so that the declared source and the odor plume it generates do not interfere with the effects of other existing plumes, allowing the localization of the remaining sources. Exploration and plume tracking by the robots is achieved using a decentralized asynchronous particle swarm optimization algorithm. The divergence operator is used to declare the odor sources. A set of simulations and real world experiments are performed on two different scenarios on a controlled environment using a swarm of 5 robots to validate the proposed methodology. Results show that the virtual plume cancelation algorithm can be successfully used to find multiple odor sources, even when two plumes overlap. It can also extend the operation of many odor source localization algorithms developed for single source localization.

/pdf/virtual-cancelation-plume-for-multiple-odor-source-28qm4kwcn9.pdf

Virtual cancelation plume for multiple odor source localization

In this article we study the convergence of the positions of a multi-agent system in a cyclic pursuit under asynchronism and time delays Each agent is assumed to operate on an infinite sequence of behaviors modeled by a finite state machine, which is represented by a discrete asynchronous mathematical model on a higher-level The results on the convergence of the synchronous model are used in the proof of convergence of the asynchronous system Numerical simulations are also performed to verify the theoretical results.

Asynchronous cyclic pursuit

In this article we consider the problem of moving in a predefined formation along a reference trajectory in the presence of disturbances in a class of multi-agent systems. The reference trajectory is generated by a neutrally stable exosystem with unknown parameters. The problem is formulated as nonlinear servomechanism problem and an adaptive internal model based controller is used to solve this problem. The performance of the system is verified with simple numerical simulations.

Veysel Gazi

Papers

Formation control of a multi-agent system using decentralized nonlinear servomechanism

Adaptive formation control and target tracking in a class of multi-agent systems: Formation maneuvers

Virtual cancelation plume for multiple odor source localization

Asynchronous cyclic pursuit

Adaptive internal model based formation control of a class of multi-agent systems