2,245 research outputs found
Distributed Adaptive Fault-Tolerant Control of Uncertain Multi-Agent Systems
This paper presents an adaptive fault-tolerant control (FTC) scheme for a
class of nonlinear uncertain multi-agent systems. A local FTC scheme is
designed for each agent using local measurements and suitable information
exchanged between neighboring agents. Each local FTC scheme consists of a fault
diagnosis module and a reconfigurable controller module comprised of a baseline
controller and two adaptive fault-tolerant controllers activated after fault
detection and after fault isolation, respectively. Under certain assumptions,
the closed-loop system's stability and leader-follower consensus properties are
rigorously established under different modes of the FTC system, including the
time-period before possible fault detection, between fault detection and
possible isolation, and after fault isolation
Adaptive Network Dynamics and Evolution of Leadership in Collective Migration
The evolution of leadership in migratory populations depends not only on
costs and benefits of leadership investments but also on the opportunities for
individuals to rely on cues from others through social interactions. We derive
an analytically tractable adaptive dynamic network model of collective
migration with fast timescale migration dynamics and slow timescale adaptive
dynamics of individual leadership investment and social interaction. For large
populations, our analysis of bifurcations with respect to investment cost
explains the observed hysteretic effect associated with recovery of migration
in fragmented environments. Further, we show a minimum connectivity threshold
above which there is evolutionary branching into leader and follower
populations. For small populations, we show how the topology of the underlying
social interaction network influences the emergence and location of leaders in
the adaptive system. Our model and analysis can describe other adaptive network
dynamics involving collective tracking or collective learning of a noisy,
unknown signal, and likewise can inform the design of robotic networks where
agents use decentralized strategies that balance direct environmental
measurements with agent interactions.Comment: Submitted to Physica D: Nonlinear Phenomen
Joint Centrality Distinguishes Optimal Leaders in Noisy Networks
We study the performance of a network of agents tasked with tracking an
external unknown signal in the presence of stochastic disturbances and under
the condition that only a limited subset of agents, known as leaders, can
measure the signal directly. We investigate the optimal leader selection
problem for a prescribed maximum number of leaders, where the optimal leader
set minimizes total system error defined as steady-state variance about the
external signal. In contrast to previously established greedy algorithms for
optimal leader selection, our results rely on an expression of total system
error in terms of properties of the underlying network graph. We demonstrate
that the performance of any given set of leaders depends on their influence as
determined by a new graph measure of centrality of a set. We define the of a set of nodes in a network graph such that a leader set with
maximal joint centrality is an optimal leader set. In the case of a single
leader, we prove that the optimal leader is the node with maximal information
centrality. In the case of multiple leaders, we show that the nodes in the
optimal leader set balance high information centrality with a coverage of the
graph. For special cases of graphs, we solve explicitly for optimal leader
sets. We illustrate with examples.Comment: Conditionally accepted to IEEE TCN
Distributed adaptive fault-tolerant leader-following formation control of nonlinear uncertain second-order multi-agent systems
This paper presents a distributed integrated fault diagnosis and accommodation scheme for leaderâfollowing formation control of a class of nonlinear uncertain secondâorder multiâagent systems. The fault model under consideration includes both process and actuator faults, which may evolve abruptly or incipiently. The timeâvarying leader communicates with a small subset of follower agents, and each follower agent communicates to its directly connected neighbors through a bidirectional network with possibly asymmetric weights. A local fault diagnosis and accommodation component are designed for each agent in the distributed system, which consists of a fault detection and isolation module and a reconfigurable controller module comprised of a baseline controller and two adaptive faultâtolerant controllers, activated after fault detection and after fault isolation, respectively. By using appropriately the designed Lyapunov functions, the closedâloop stability and asymptotic convergence properties of the leaderâfollower formation are rigorously established under different modes of the faultâtolerant control system
Continuum Deformation of a Multiple Quadcopter Payload Delivery Team without Inter-Agent Communication
This paper proposes continuum deformation as a strategy for controlling the
collective motion of a multiple quadcopter system (MQS) carrying a common
payload. Continuum deformation allows expansion and contraction of inter-agent
distances in a 2D motion plane to follow desired motions of three team leaders.
The remaining quadcopter followers establish the desired continuum deformation
only by knowing leaders positions at desired sample time waypoints without the
need for inter-agent communication over the intermediate intervals. Each
quadcopter applies a linear-quadratic-Gaussian (LQG) controller to track the
desired trajectory given by the continuum deformation in the presence of
disturbance and measurement noise. Results of simulated cooperative aerial
payload transport in the presence of uncertainty illustrate the application of
continuum deformation for coordinated transport through a narrow channel
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