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

Connectivity Preservation in Nonholonomic Multi-Agent Systems: A Bounded Distributed Control Strategy

This technical note is concerned with the connectivity preservation of a group of unicycles using a novel distributed control scheme. The proposed local controllers are bounded, and are capable of maintaining the connectivity of those pairs of agents which are initially within the connectivity range. This means that if the network of agents is initially connected, it will remain connected at all times under this control law. Each local controller is designed in such a way that when an agent is about to lose connectivity with a neighbor, the lowest-order derivative of the agent's position that is neither zero nor perpendicular to the edge connecting the agent to the corresponding neighbor, makes an acute angle with this edge, which is shown to result in shrinking the edge. The proposed methodology is then used to develop bounded connectivity preserving control strategies for the consensus problem as one of the unprecedented contributions of this work. The theoretical results are validated by simulation

Hybrid Flocking Control Algorithm with Application to Coordination between Multiple Fixed-wing Aircraft

Flocking, as a collective behavior of a group, has been investigated in many areas, and in the recent decade, flocking algorithm design has gained a lot of attention due to its variety of potential applications. Although there are many applications exclusively related to fixed-wing aircraft, most of the theoretical works rarely consider these situations. The fixed-wing aircraft flocking is distinct from the general flocking problems by four practical concerns, which include the nonholonomic constraint, the limitation of speed, the collision avoidance and the efficient use of airspace. None of the existing works have addressed all these concerns. The major difficulty is to take into account the all four concerns simultaneously meanwhile having a relatively mild requirement on the initial states of aircraft. In this thesis, to solve the fixed-wing aircraft flocking problem, a supervisory decentralized control algorithm is proposed. The proposed control algorithm has a switching control structure, which basically includes three modes of control protocol and a state-dependent switching logic. Three modes of decentralized control protocol are designed based on the artificial potential field method, which helps to address the nonholonomic constraint, the limitation of speed and the collision avoidance for appropriate initial conditions. The switching logic is designed based on the invariance property induced by the control modes such that the desirable convergence properties of the flocking behavior and the efficient use of airspace are addressed. The proposed switching logic can avoid the fast mode switching, and the supervisor does not require to perform switchings frequently and respond to the aircraft immediately, which means the desired properties can still be guaranteed with the presence of the dwell time in the supervisor

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

Leader-Following consensus for nonlinear agents with measurement feedback

The leader-following consensus problem is investigated for large classes of nonlinear identical agents. Sufficient conditions are provided for achieving consensus via state and measurement feedback laws based on a local (ie, among neighbors) information exchange. The leader's trajectories are assumed bounded without knowledge of the containing compact set and the agents' trajectories possibly unbounded under the action of a bounded input. Generalizations to heterogeneous agents and robustness are also discussed

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

Analysis of path following and obstacle avoidance for multiple wheeled robots in a shared workspace

The article presents the experimental evaluation of an integrated approach for path following and obstacle avoidance, implemented on wheeled robots. Wheeled robots are widely used in many different contexts, and they are usually required to operate in partial or total autonomy: in a wide range of situations, having the capability to follow a predetermined path and avoiding unexpected obstacles is extremely relevant. The basic requirement for an appropriate collision avoidance strategy is to sense or detect obstacles and make proper decisions when the obstacles are nearby. According to this rationale, the approach is based on the definition of the path to be followed as a curve on the plane expressed in its implicit form f(x, y) = 0, which is fed to a feedback controller for path following. Obstacles are modeled through Gaussian functions that modify the original function, generating a resulting safe path which - once again - is a curve on the plane expressed as f\u2032(x, y) = 0: the deformed path can be fed to the same feedback controller, thus guaranteeing convergence to the path while avoiding all obstacles. The features and performance of the proposed algorithm are confirmed by experiments in a crowded area with multiple unicycle-like robots and moving persons