1,396 research outputs found
Controlling rigid formations of mobile agents under inconsistent measurements
Despite the great success of using gradient-based controllers to stabilize
rigid formations of autonomous agents in the past years, surprising yet
intriguing undesirable collective motions have been reported recently when
inconsistent measurements are used in the agents' local controllers. To make
the existing gradient control robust against such measurement inconsistency, we
exploit local estimators following the well known internal model principle for
robust output regulation control. The new estimator-based gradient control is
still distributed in nature and can be constructed systematically even when the
number of agents in a rigid formation grows. We prove rigorously that the
proposed control is able to guarantee exponential convergence and then
demonstrate through robotic experiments and computer simulations that the
reported inconsistency-induced orbits of collective movements are effectively
eliminated.Comment: 10 page
Decentralized Formation Control with A Quadratic Lyapunov Function
In this paper, we investigate a decentralized formation control algorithm for
an undirected formation control model. Unlike other formation control problems
where only the shape of a configuration counts, we emphasize here also its
Euclidean embedding. By following this decentralized formation control law, the
agents will converge to certain equilibrium of the control system. In
particular, we show that there is a quadratic Lyapunov function associated with
the formation control system whose unique local (global) minimum point is the
target configuration. In view of the fact that there exist multiple equilibria
(in fact, a continuum of equilibria) of the formation control system, and hence
there are solutions of the system which converge to some equilibria other than
the target configuration, we apply simulated annealing, as a heuristic method,
to the formation control law to fix this problem. Simulation results show that
sample paths of the modified stochastic system approach the target
configuration
Agreement Problems in Networks with Directed Graphs and Switching Topology
In this paper, we provide tools for convergence and performance analysis of an agreement protocol for a network of integrator agents with directed information flow. Moreover, we analyze algorithmic robustness of this consensus protocol for the case of a network with mobile nodes and switching topology. We establish a connection between the Fiedler eigenvalue of the graph Laplacian and the performance of this agreement protocol. We demostrate that a class of directed graphs, called balanced graphs, have a crucial role in solving average-consensus problems. Based on the properties of balanced graphs, a group disagreement function (i.e. Lyapunov function) is proposed for convergence analysis of this agreement protocol for networks with directed graphs. This group disagreement function is later used for convergence analysis for the agreement problem in networks with switching topology. We provide simulation results that are consistent with our theoretical results and demonstrate the effectiveness of the proposed analytical tools
Consensus problems in networks of agents with switching topology and time-delays
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
Robustness issues in double-integrator undirected rigid formation systems
In this paper we consider rigid formation control systems modelled by double integrators (including formation stabilization systems and flocking control systems), with a focus on their robustness property in the presence of distance mismatch. By introducing additional state variables we show the augmented double-integrator distance error system is self-contained, and we prove the exponential stability of the distance error systems via linearization analysis. As a consequence of the exponential stability, the distance error still converges in the presence of small and constant distance mismatches, while additional motions of the resulted formation will occur. We further analyze the rigid motions induced by constant mismatches for both double-integrator formation stabilisation systems and flocking control systems.This work was supported by the Australian Research Council (ARC) under grant DP130103610 and DP160104500. Z. Sun was supported by the Australian Prime Minister's Endeavour Postgraduate Award from Australian Government. The work of S. Mou was supported by funding from Northrop Grumman Corporation
Taming mismatches in inter-agent distances for the formation-motion control of second-order agents
This paper presents the analysis on the influence of distance mismatches on
the standard gradient-based rigid formation control for second-order agents. It
is shown that, similar to the first-order case as recently discussed in the
literature, these mismatches introduce two undesired group behaviors: a
distorted final shape and a steady-state motion of the group formation. We show
that such undesired behaviors can be eliminated by combining the standard
formation control law with distributed estimators. Finally, we show how the
mismatches can be effectively employed as design parameters in order to control
a combined translational and rotational motion of the formation.Comment: 14 pages, conditionally accepted in Automatic Control, IEEE
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Distributed stabilization control of rigid formations with prescribed orientation
Most rigid formation controllers reported in the literature aim to only
stabilize a rigid formation shape, while the formation orientation is not
controlled. This paper studies the problem of controlling rigid formations with
prescribed orientations in both 2-D and 3-D spaces. The proposed controllers
involve the commonly-used gradient descent control for shape stabilization, and
an additional term to control the directions of certain relative position
vectors associated with certain chosen agents. In this control framework, we
show the minimal number of agents which should have knowledge of a global
coordinate system (2 agents for a 2-D rigid formation and 3 agents for a 3-D
rigid formation), while all other agents do not require any global coordinate
knowledge or any coordinate frame alignment to implement the proposed control.
The exponential convergence to the desired rigid shape and formation
orientation is also proved. Typical simulation examples are shown to support
the analysis and performance of the proposed formation controllers.Comment: This paper was submitted to Automatica for publication. Compared to
the submitted version, this arXiv version contains complete proofs, examples
and remarks (some of them are removed in the submitted version due to space
limit.
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