174 research outputs found
Multi-agent Systems with Compasses
This paper investigates agreement protocols over cooperative and
cooperative--antagonistic multi-agent networks with coupled continuous-time
nonlinear dynamics. To guarantee convergence for such systems, it is common in
the literature to assume that the vector field of each agent is pointing inside
the convex hull formed by the states of the agent and its neighbors, given that
the relative states between each agent and its neighbors are available. This
convexity condition is relaxed in this paper, as we show that it is enough that
the vector field belongs to a strict tangent cone based on a local supporting
hyperrectangle. The new condition has the natural physical interpretation of
requiring shared reference directions in addition to the available local
relative states. Such shared reference directions can be further interpreted as
if each agent holds a magnetic compass indicating the orientations of a global
frame. It is proven that the cooperative multi-agent system achieves
exponential state agreement if and only if the time-varying interaction graph
is uniformly jointly quasi-strongly connected. Cooperative--antagonistic
multi-agent systems are also considered. For these systems, the relation has a
negative sign for arcs corresponding to antagonistic interactions. State
agreement may not be achieved, but instead it is shown that all the agents'
states asymptotically converge, and their limits agree componentwise in
absolute values if and in general only if the time-varying interaction graph is
uniformly jointly strongly connected.Comment: SIAM Journal on Control and Optimization, In pres
COORDINATION OF LEADER-FOLLOWER MULTI-AGENT SYSTEM WITH TIME-VARYING OBJECTIVE FUNCTION
This thesis aims to introduce a new framework for the distributed control of multi-agent systems with adjustable swarm control objectives. Our goal is twofold: 1) to provide an overview to how time-varying objectives in the control of autonomous systems may be applied to the distributed control of multi-agent systems with variable autonomy level, and 2) to introduce a framework to incorporate the proposed concept to fundamental swarm behaviors such as aggregation and leader tracking. Leader-follower multi-agent systems are considered in this study, and a general form of time-dependent artificial potential function is proposed to describe the varying objectives of the system in the case of complete information exchange. Using Lyapunov methods, the stability and boundedness of the agents\u27 trajectories under single order and higher order dynamics are analyzed. Illustrative numerical simulations are presented to demonstrate the validity of our results. Then, we extend these results for multi-agent systems with limited information exchange and switching communication topology. The first steps of the realization of an experimental framework have been made with the ultimate goal of verifying the simulation results in practice
On the genericity properties in networked estimation: Topology design and sensor placement
In this paper, we consider networked estimation of linear, discrete-time
dynamical systems monitored by a network of agents. In order to minimize the
power requirement at the (possibly, battery-operated) agents, we require that
the agents can exchange information with their neighbors only \emph{once per
dynamical system time-step}; in contrast to consensus-based estimation where
the agents exchange information until they reach a consensus. It can be
verified that with this restriction on information exchange, measurement fusion
alone results in an unbounded estimation error at every such agent that does
not have an observable set of measurements in its neighborhood. To over come
this challenge, state-estimate fusion has been proposed to recover the system
observability. However, we show that adding state-estimate fusion may not
recover observability when the system matrix is structured-rank (-rank)
deficient.
In this context, we characterize the state-estimate fusion and measurement
fusion under both full -rank and -rank deficient system matrices.Comment: submitted for IEEE journal publicatio
Bipartite Consensus for a Class of Nonlinear Multi-agent Systems Under Switching Topologies:A Disturbance Observer-Based Approach
This paper considers the leader-following bipartite consensus for a class of nonlinear multi-agent systems (MASs) subject to exogenous disturbances under directed fixed and switching topologies, respectively. Firstly, two new output feedback control protocols involving signs of link weights are introduced based on relative output measurements of neighboring agents. In order to estimate the disturbances produced by an exogenous system, a disturbance observer-based approach is developed. Then, sufficient conditions for leader-following bipartite consensus with directed fixed topologies are derived. Furthermore, by assuming that each switching topology contains a directed spanning tree, it is proved that the leader-following bipartite consensus can be realized with the designed output feedback control protocol if the dwell time is larger than a non-negative threshold. Finally, numerical simulations inspired by a real-world DC motors are provided to illustrate the effectiveness of the proposed controllers
Leader-following Consensus Control of a Distributed Linear Multi-agent System using a Sliding Mode Strategy
A distributed leader-following consensus control framework is proposed for a linear system. The linear system is first transformed into a regular form. Then a linear sliding mode is designed to provide high robustness, and the corresponding consensus protocol is proposed in a fully distributed fashion. When matched disturbances are present, it can be demonstrated that the system states reach the sliding mode in finite time and consensus can be achieved asymptotically using Lyapunov theory and the invariant set theorem. Simulation results validate the effectiveness of the proposed algorithm
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