4,312 research outputs found
Output consensus of nonlinear multi-agent systems with unknown control directions
In this paper, we consider an output consensus problem for a general class of
nonlinear multi-agent systems without a prior knowledge of the agents' control
directions. Two distributed Nussbaumtype control laws are proposed to solve the
leaderless and leader-following adaptive consensus for heterogeneous multiple
agents. Examples and simulations are given to verify their effectivenessComment: 10 pages;2 figure
Cooperative Adaptive Control for Cloud-Based Robotics
This paper studies collaboration through the cloud in the context of
cooperative adaptive control for robot manipulators. We first consider the case
of multiple robots manipulating a common object through synchronous centralized
update laws to identify unknown inertial parameters. Through this development,
we introduce a notion of Collective Sufficient Richness, wherein parameter
convergence can be enabled through teamwork in the group. The introduction of
this property and the analysis of stable adaptive controllers that benefit from
it constitute the main new contributions of this work. Building on this
original example, we then consider decentralized update laws, time-varying
network topologies, and the influence of communication delays on this process.
Perhaps surprisingly, these nonidealized networked conditions inherit the same
benefits of convergence being determined through collective effects for the
group. Simple simulations of a planar manipulator identifying an unknown load
are provided to illustrate the central idea and benefits of Collective
Sufficient Richness.Comment: ICRA 201
Event-triggering architectures for adaptive control of uncertain dynamical systems
In this dissertation, new approaches are presented for the design and implementation of networked adaptive control systems to reduce the wireless network utilization while guaranteeing system stability in the presence of system uncertainties. Specifically, the design and analysis of state feedback adaptive control systems over wireless networks using event-triggering control theory is first presented. The state feedback adaptive control results are then generalized to the output feedback case for dynamical systems with unmeasurable state vectors. This event-triggering approach is then adopted for large-scale uncertain dynamical systems. In particular, decentralized and distributed adaptive control methodologies are proposed with reduced wireless network utilization with stability guarantees.
In addition, for systems in the absence of uncertainties, a new observer-free output feedback cooperative control architecture is developed. Specifically, the proposed architecture is predicated on a nonminimal state-space realization that generates an expanded set of states only using the filtered input and filtered output and their derivatives for each vehicle, without the need for designing an observer for each vehicle. Building on the results of this new observer-free output feedback cooperative control architecture, an event-triggering methodology is next proposed for the output feedback cooperative control to schedule the exchanged output measurements information between the agents in order to reduce wireless network utilization. Finally, the output feedback cooperative control architecture is generalized to adaptive control for handling exogenous disturbances in the follower vehicles.
For each methodology, the closed-loop system stability properties are rigorously analyzed, the effect of the user-defined event-triggering thresholds and the controller design parameters on the overall system performance are characterized, and Zeno behavior is shown not to occur with the proposed algorithms --Abstract, page iv
Similarity Decomposition Approach to Oscillatory Synchronization for Multiple Mechanical Systems With a Virtual Leader
This paper addresses the oscillatory synchronization problem for multiple
uncertain mechanical systems with a virtual leader, and the interaction
topology among them is assumed to contain a directed spanning tree. We propose
an adaptive control scheme to achieve the goal of oscillatory synchronization.
Using the similarity decomposition approach, we show that the position and
velocity synchronization errors between each mechanical system (or follower)
and the virtual leader converge to zero. The performance of the proposed
adaptive scheme is shown by numerical simulation results.Comment: 15 pages, 3 figures, published in 2014 Chinese Control Conferenc
Periodic event-triggered output regulation for linear multi-agent systems
This study considers the problem of periodic event-triggered (PET)
cooperative output regulation for a class of linear multi-agent systems. The
advantage of the PET output regulation is that the data transmission and
triggered condition are only needed to be monitored at discrete sampling
instants. It is assumed that only a small number of agents can have access to
the system matrix and states of the leader. Meanwhile, the PET mechanism is
considered not only in the communication between various agents, but also in
the sensor-to-controller and controller-to-actuator transmission channels for
each agent. The above problem set-up will bring some challenges to the
controller design and stability analysis. Based on a novel PET distributed
observer, a PET dynamic output feedback control method is developed for each
follower. Compared with the existing works, our method can naturally exclude
the Zeno behavior, and the inter-event time becomes multiples of the sampling
period. Furthermore, for every follower, the minimum inter-event time can be
determined \textit{a prior}, and computed directly without the knowledge of the
leader information. An example is given to verify and illustrate the
effectiveness of the new design scheme.Comment: 17 pages, 13 figures, submitted to Automatica. accepte
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