Connectivity Preservation in Distributed Control of Multi-Agent Systems

The problem of designing bounded distributed connectivity preserving control strategies for multi-agent systems is studied in this work. In distributed control of multi-agent systems, each agent is required to measure some variables of other agents, or a subset of them. Such variables include, for example, relative positions, relative velocities, and headings of the neighboring agents. One of the main assumptions in this type of systems is the connectivity of the corresponding network. Therefore, regardless of the overall objective, the designed control laws should preserve the network connectivity, which is usually a distance-dependent condition. The designed controllers should also be bounded because in practice the actuators of the agents can only handle finite forces or torques. This problem is investigated for two cases of single-integrator agents and unicycles, using a novel class of distributed potential functions. The proposed controllers maintain the connectivity of the agents that are initially in the connectivity range. Therefore, if the network is initially connected, it will remain connected at all times. The results are first developed for a static information flow graph, and then extended to the case of dynamic edge addition. Connectivity preservation for problems involving static leaders is covered as well. The potential functions are chosen to be smooth, resulting in bounded control inputs. These functions are subsequently used to develop connectivity preserving controllers for the consensus and containment problems. Collision avoidance is investigated as another relevant problem, where a bounded distributed swarm aggregation strategy with both connectivity preservation and collision avoidance properties is presented. Simulations are provided throughout the work to support the theoretical findings

Error Analysis in Multi-Agent Control Systems

Any cooperative control scheme relies on some measurements which are often assumed to be exact to simplify the analysis. However, it is known that in practice all measured quantities are subject to error, which can deteriorate the overall performance of the network significantly. This work proposes a new measurement error analysis in the control of multi-agent systems. In particular, the connectivity preservation of multi-agent systems with state-dependent error in distance measurements is considered. It is assumed that upper bounds on the measurement error and its rate of change are available. A general class of distributed control strategies is then proposed for the distance-dependent connectivity preservation of the agents in the network. It is shown that if two neighboring agents are initially located in the connectivity range, they are guaranteed to remain connected at all times. Furthermore, the formation control problem for a team of single-integrator agents subject to distance measurement error is investigated using navigation functions. Collision, obstacle and boundary avoidance are important features of the proposed strategy. Conditions on the magnitude of the measurement error and its rate of change are derived under which a new error-dependent formation can be achieved anywhere in the space. The effectiveness of the proposed control strategies in consensus and containment problems is demonstrated by simulation

Robust Connectivity Analysis for Multi-Agent Systems

In this report we provide a decentralized robust control approach, which guarantees that connectivity of a multi-agent network is maintained when certain bounded input terms are added to the control strategy. Our main motivation for this framework is to determine abstractions for multi-agent systems under coupled constraints which are further exploited for high level plan generation.Comment: 20 page

Bounded Distributed Flocking Control of Nonholonomic Mobile Robots

There have been numerous studies on the problem of flocking control for multiagent systems whose simplified models are presented in terms of point-mass elements. Meanwhile, full dynamic models pose some challenging problems in addressing the flocking control problem of mobile robots due to their nonholonomic dynamic properties. Taking practical constraints into consideration, we propose a novel approach to distributed flocking control of nonholonomic mobile robots by bounded feedback. The flocking control objectives consist of velocity consensus, collision avoidance, and cohesion maintenance among mobile robots. A flocking control protocol which is based on the information of neighbor mobile robots is constructed. The theoretical analysis is conducted with the help of a Lyapunov-like function and graph theory. Simulation results are shown to demonstrate the efficacy of the proposed distributed flocking control scheme

Connectivity-Preserving Swarm Teleoperation With A Tree Network

During swarm teleoperation, the human operator may threaten the distance-dependent inter-robot communications and, with them, the connectivity of the slave swarm. To prevent the harmful component of the human command from disconnecting the swarm network, this paper develops a constructive strategy to dynamically modulate the interconnections of, and the locally injected damping at, all slave robots. By Lyapunov-based set invariance analysis, the explicit law for updating that control gains has been rigorously proven to synchronize the slave swarm while preserving all interaction links in the tree network. By properly limiting the impact of the user command rather than rejecting it entirely, the proposed control law enables the human operator to guide the motion of the slave swarm to the extent to which it does not endanger the connectivity of the swarm network. Experiment results demonstrate that the proposed strategy can maintain the connectivity of the tree network during swarm teleoperation