18,053 research outputs found
Finite-Time Resilient Formation Control with Bounded Inputs
In this paper we consider the problem of a multi-agent system achieving a
formation in the presence of misbehaving or adversarial agents. We introduce a
novel continuous time resilient controller to guarantee that normally behaving
agents can converge to a formation with respect to a set of leaders. The
controller employs a norm-based filtering mechanism, and unlike most prior
algorithms, also incorporates input bounds. In addition, the controller is
shown to guarantee convergence in finite time. A sufficient condition for the
controller to guarantee convergence is shown to be a graph theoretical
structure which we denote as Resilient Directed Acyclic Graph (RDAG). Further,
we employ our filtering mechanism on a discrete time system which is shown to
have exponential convergence. Our results are demonstrated through simulations
Distributed Delay-Tolerant Strategies for Equality-Constraint Sum-Preserving Resource Allocation
This paper proposes two nonlinear dynamics to solve constrained distributed
optimization problem for resource allocation over a multi-agent network. In
this setup, coupling constraint refers to resource-demand balance which is
preserved at all-times. The proposed solutions can address various model
nonlinearities, for example, due to quantization and/or saturation. Further, it
allows to reach faster convergence or to robustify the solution against
impulsive noise or uncertainties. We prove convergence over weakly connected
networks using convex analysis and Lyapunov theory. Our findings show that
convergence can be reached for general sign-preserving odd nonlinearity. We
further propose delay-tolerant mechanisms to handle general bounded
heterogeneous time-varying delays over the communication network of agents
while preserving all-time feasibility. This work finds application in CPU
scheduling and coverage control among others. This paper advances the
state-of-the-art by addressing (i) possible nonlinearity on the agents/links,
meanwhile handling (ii) resource-demand feasibility at all times, (iii)
uniform-connectivity instead of all-time connectivity, and (iv) possible
heterogeneous and time-varying delays. To our best knowledge, no existing work
addresses contributions (i)-(iv) altogether. Simulations and comparative
analysis are provided to corroborate our contributions
A review of Multi-Agent Simulation Models in Agriculture
Multi-Agent Simulation (MAS) models are intended to capture emergent properties of complex systems that are not amenable to equilibrium analysis. They are beginning to see some use for analysing agricultural systems. The paper reports on work in progress to create a MAS for specific sectors in New Zealand agriculture. One part of the paper focuses on options for modelling land and other resources such as water, labour and capital in this model, as well as markets for exchanging resources and commodities. A second part considers options for modelling agent heterogeneity, especially risk preferences of farmers, and the impacts on decision-making. The final section outlines the MAS that the authors will be constructing over the next few years and the types of research questions that the model will help investigate.multi-agent simulation models, modelling, agent-based model, cellular automata, decision-making, Crop Production/Industries, Environmental Economics and Policy, Farm Management, Land Economics/Use, Livestock Production/Industries,
Optimal Time-Invariant Distributed Formation Tracking for Second-Order Multi-Agent Systems
This paper addresses the optimal time-invariant formation tracking problem
with the aim of providing a distributed solution for multi-agent systems with
second-order integrator dynamics. In the literature, most of the results
related to multi-agent formation tracking do not consider energy issues while
investigating distributed feedback control laws. In order to account for this
crucial design aspect, we contribute by formalizing and proposing a solution to
an optimization problem that encapsulates trajectory tracking, distance-based
formation control, and input energy minimization, through a specific and key
choice of potential functions in the optimization cost. To this end, we show
how to compute the inverse dynamics in a centralized fashion by means of the
Projector-Operator-based Newton's method for Trajectory Optimization (PRONTO)
and, more importantly, we exploit such an offline solution as a general
reference to devise a novel online distributed control law. Finally, numerical
examples involving a cubic formation following a straight path in the 3D space
are provided to validate the proposed control strategies.Comment: 28 pages, 2 figures, submitted to the European Journal of Control on
June 23rd, 2023 (version 1
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
Distributed Fault-Tolerant Consensus Tracking Control of Multi-Agent Systems under Fixed and Switching Topologies
This paper proposes a novel distributed fault-tolerant consensus tracking control design for multi-agent systems with abrupt and incipient actuator faults under fixed and switching topologies. The fault and state information of each individual agent is estimated by merging unknown input observer in the decentralized fault estimation hierarchy. Then, two kinds of distributed fault-tolerant consensus tracking control schemes with average dwelling time technique are developed to guarantee the mean-square exponential consensus convergence of multi-agent systems, respectively, on the basis of the relative neighboring output information as well as the estimated information in fault estimation. Simulation results demonstrate the effectiveness of the proposed fault-tolerant consensus tracking control algorithm
Resilient Output Consensus Control of Heterogeneous Multi-agent Systems against Byzantine Attacks: A Twin Layer Approach
This paper studies the problem of cooperative control of heterogeneous
multi-agent systems (MASs) against Byzantine attacks. The agent affected by
Byzantine attacks sends different wrong values to all neighbors while applying
wrong input signals for itself, which is aggressive and difficult to be
defended. Inspired by the concept of Digital Twin, a new hierarchical protocol
equipped with a virtual twin layer (TL) is proposed, which decouples the above
problems into the defense scheme against Byzantine edge attacks on the TL and
the defense scheme against Byzantine node attacks on the cyber-physical layer
(CPL). On the TL, we propose a resilient topology reconfiguration strategy by
adding a minimum number of key edges to improve network resilience. It is
strictly proved that the control strategy is sufficient to achieve asymptotic
consensus in finite time with the topology on the TL satisfying strongly
-robustness. On the CPL, decentralized chattering-free controllers are
proposed to guarantee the resilient output consensus for the heterogeneous MASs
against Byzantine node attacks. Moreover, the obtained controller shows
exponential convergence. The effectiveness and practicality of the theoretical
results are verified by numerical examples
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
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