2,468 research outputs found
Stabilization of systems with asynchronous sensors and controllers
We study the stabilization of networked control systems with asynchronous
sensors and controllers. Offsets between the sensor and controller clocks are
unknown and modeled as parametric uncertainty. First we consider multi-input
linear systems and provide a sufficient condition for the existence of linear
time-invariant controllers that are capable of stabilizing the closed-loop
system for every clock offset in a given range of admissible values. For
first-order systems, we next obtain the maximum length of the offset range for
which the system can be stabilized by a single controller. Finally, this bound
is compared with the offset bounds that would be allowed if we restricted our
attention to static output feedback controllers.Comment: 32 pages, 6 figures. This paper was partially presented at the 2015
American Control Conference, July 1-3, 2015, the US
Event-driven observer-based smart-sensors for output feedback control of linear systems
This paper deals with a recent design of event-driven observer-based smart sensors for output feedback control of linear systems. We re-design the triggering mechanism proposed in a previously reported system with the implementation of self-sampling data smart sensors; as a result, we improve its performance. Our approach is theoretically supported by using Lyapunov theory and numerically evidenced by controlling the inverted pendulum on the cart mechanism.Postprint (published version
On Resilient Control of Nonlinear Systems under Denial-of-Service
We analyze and design a control strategy for nonlinear systems under
Denial-of-Service attacks. Based on an ISS-Lyapunov function analysis, we
provide a characterization of the maximal percentage of time during which
feedback information can be lost without resulting in the instability of the
system. Motivated by the presence of a digital channel we consider event-based
controllers for which a minimal inter-sampling time is explicitly
characterized.Comment: 7 pages, 1 figur
Output-Feedback Synthesis for a Class of Aperiodic Impulsive Systems
We derive novel criteria for designing stabilizing dynamic output-feedback
controllers for a class of aperiodic impulsive systems subject to a range
dwell-time condition. Our synthesis conditions are formulated as
clock-dependent linear matrix inequalities (LMIs) which can be solved
numerically, e.g., by using matrix sum-of-squares relaxation methods. We show
that our results allow us to design dynamic output-feedback controllers for
aperiodic sample-data systems and illustrate the proposed approach by means of
a numerical example
Data-driven estimation of the maximum sampling interval: analysis and controller design for discrete-time systems
This article is concerned with data-driven analysis of discrete-time systems
under aperiodic sampling, and in particular with a data-driven estimation of
the maximum sampling interval (MSI). The MSI is relevant for analysis of and
controller design for cyber-physical, embedded and networked systems, since it
gives a limit on the time span between sampling instants such that stability is
guaranteed. We propose tools to compute the MSI for a given controller and to
design a controller with a preferably large MSI, both directly from a
finite-length, noise-corrupted state-input trajectory of the system. We follow
two distinct approaches for stability analysis, one taking a robust control
perspective and the other a switched systems perspective on the aperiodically
sampled system. In a numerical example and a subsequent discussion, we
demonstrate the efficacy of our developed tools and compare the two approaches.Comment: 16 pages, 4 figure, 1 table. Now contains 1) a disturbance
description via multipliers, 2) extended proofs and 3) an extensive numerical
case study, including a comparison of different data lengths, a discussion of
complexity and a comparison with set membership estimatio
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