Adaptive rendezvous of multiple mobile agents with nonlinear dynamics and preserved network connectivity

This paper investigates rendezvous of multiple nonlinear dynamical mobile agents with a virtual leader in a dynamic proximity network. It is assumed that only a fraction of agents in the group have access to the information on the position and velocity of the virtual leader. To avoid fragmentation, a bounded connectivity-preserving rendezvous algorithm is proposed for the multi-agent systems. Under the assumption that the initial network is connected, local adaptation strategies for the rendezvous algorithm are introduced that enable all agents to synchronize with the virtual leader even when only one agent is informed, without requiring any knowledge of the agent dynamics. Simulation results on an example are given to numerically verify the theoretical results. © 2011 Asian Control Association.published_or_final_versio

Second-Order Consensus of Networked Mechanical Systems With Communication Delays

In this paper, we consider the second-order consensus problem for networked mechanical systems subjected to nonuniform communication delays, and the mechanical systems are assumed to interact on a general directed topology. We propose an adaptive controller plus a distributed velocity observer to realize the objective of second-order consensus. It is shown that both the positions and velocities of the mechanical agents synchronize, and furthermore, the velocities of the mechanical agents converge to the scaled weighted average value of their initial ones. We further demonstrate that the proposed second-order consensus scheme can be used to solve the leader-follower synchronization problem with a constant-velocity leader and under constant communication delays. Simulation results are provided to illustrate the performance of the proposed adaptive controllers.Comment: 16 pages, 5 figures, submitted to IEEE Transactions on Automatic Contro

An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination

This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations

Semi-global leader-following consensus of linear multi-agent systems with input saturation via low gain feedback

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Connectivity Preservation in Multi-Agent Systems using Model Predictive Control

Flocking of multiagent systems is one of the basic behaviors in the field of control of multiagent systems and it is an essential element of many real-life applications. Such systems under various network structures and environment modes have been extensively studied in the past decades. Navigation of agents in a leader-follower structure while operating in environments with obstacles is particularly challenging. One of the main challenges in flocking of multiagent systems is to preserve connectivity. Gradient descent method is widely utilized to achieve this goal. But the main shortcoming of applying this method for the leader-follower structure is the need for continuous data transmission between agents and/or the preservation of a fixed connection topology. In this research, we propose an innovative model predictive controller based on a potential field that maintains the connectivity of a flock of agents in a leader-follower structure with dynamic topology. The agents navigate through an environment with obstacles that form a path leading to a certain target. Such a control technique avoids collisions of followers with each other without using any communication links while following their leader which navigates in the environment through potential functions for modelling the neighbors and obstacles. The potential field is dynamically updated by introducing weight variables in order to preserve connectivity among the followers as we assume only the leader knows the target position. The values of these weights are changed in real-time according to trajectories of the agents when the critical neighbors of each agent is determined. We compare the performance of our predictive-control based algorithm with other approaches. The results show that our algorithm causes the agents to reach the target in less time. However, our algorithm faces more deadlock cases when the agents go through relatively narrow paths. Due to the consideration of the input costs in our controller, the group of agents reaching the target faster does not necessarily result in the followers consuming more energy than the leader

Distributed coordinate tracking control of multiple wheeled mobile robots

In this thesis, distributed coordinate tracking control of multiple wheeled-mobile robots is studied. Control algorithms are proposed for both kinematic and dynamic models. All vehicle agents share the same mechanical structure. The communication topology is leader-follower topology and the reference signal is generated by the virtual leader. We will introduce two common kinematic models of WMR and control algorithms are proposed for both kinematic models with the aid of graph theory. Since it is more realistic that the control inputs are torques so dynamic extension is studied following by the kinematics. Torque controllers are designed with the aid of backstepping method so that the velocities of the mobile robots converge to the desired velocities. Because of the fact that in practice, the inertial parameter of WMR maybe not exactly known or even unknown, so both dynamics with and without inertial uncertainties are considered in this thesis