48,007 research outputs found
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
Time-and event-driven communication process for networked control systems: A survey
Copyright © 2014 Lei Zou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In recent years, theoretical and practical research topics on networked control systems (NCSs) have gained an increasing interest from many researchers in a variety of disciplines owing to the extensive applications of NCSs in practice. In particular, an urgent need has arisen to understand the effects of communication processes on system performances. Sampling and protocol are two fundamental aspects of a communication process which have attracted a great deal of research attention. Most research focus has been on the analysis and control of dynamical behaviors under certain sampling procedures and communication protocols. In this paper, we aim to survey some recent advances on the analysis and synthesis issues of NCSs with different sampling procedures (time-and event-driven sampling) and protocols (static and dynamic protocols). First, these sampling procedures and protocols are introduced in detail according to their engineering backgrounds as well as dynamic natures. Then, the developments of the stabilization, control, and filtering problems are systematically reviewed and discussed in great detail. Finally, we conclude the paper by outlining future research challenges for analysis and synthesis problems of NCSs with different communication processes.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Co-design of output feedback laws and event-triggering conditions for linear systems
We present a procedure to simultaneously design the output feedback law and
the event-triggering condition to stabilize linear systems. The closed-loop
system is shown to satisfy a global asymptotic stability property and the
existence of a strictly positive minimum amount of time between two
transmissions is guaranteed. The event-triggered controller is obtained by
solving linear matrix inequalities (LMIs). We then exploit the flexibility of
the method to maximize the guaranteed minimum amount of time between two
transmissions. Finally, we provide a (heuristic) method to reduce the amount of
transmissions, which is supported by numerical simulations
Multiple Loop Self-Triggered Model Predictive Control for Network Scheduling and Control
We present an algorithm for controlling and scheduling multiple linear
time-invariant processes on a shared bandwidth limited communication network
using adaptive sampling intervals. The controller is centralized and computes
at every sampling instant not only the new control command for a process, but
also decides the time interval to wait until taking the next sample. The
approach relies on model predictive control ideas, where the cost function
penalizes the state and control effort as well as the time interval until the
next sample is taken. The latter is introduced in order to generate an adaptive
sampling scheme for the overall system such that the sampling time increases as
the norm of the system state goes to zero. The paper presents a method for
synthesizing such a predictive controller and gives explicit sufficient
conditions for when it is stabilizing. Further explicit conditions are given
which guarantee conflict free transmissions on the network. It is shown that
the optimization problem may be solved off-line and that the controller can be
implemented as a lookup table of state feedback gains. Simulation studies which
compare the proposed algorithm to periodic sampling illustrate potential
performance gains.Comment: Accepted for publication in IEEE Transactions on Control Systems
Technolog
Event-Triggered Observers and Observer-Based Controllers for a Class of Nonlinear Systems
In this paper, we investigate the stabilization of a nonlinear plant subject
to network constraints, under the assumption of partial knowledge of the plant
state. The event triggered paradigm is used for the observation and the control
of the system. Necessary conditions, making use of the ISS property, are given
to guarantee the existence of a triggering mechanism, leading to asymptotic
convergence of the observer and system states. The proposed triggering
mechanism is illustrated in the stabilization of a robot with a flexible link
robot.Comment: Proceedings of the 2015 American Control Conference - ACC 201
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