12,596 research outputs found
Mathematical control of complex systems
Copyright © 2013 ZidongWang 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
New advances in H∞ control and filtering for nonlinear systems
The main objective of this special issue is to
summarise recent advances in H∞ control and filtering
for nonlinear systems, including time-delay, hybrid and
stochastic systems. The published papers provide new
ideas and approaches, clearly indicating the advances
made in problem statements, methodologies or applications
with respect to the existing results. The special
issue also includes papers focusing on advanced and
non-traditional methods and presenting considerable
novelties in theoretical background or experimental
setup. Some papers present applications to newly
emerging fields, such as network-based control and
estimation
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
Towards Scalable Synthesis of Stochastic Control Systems
Formal control synthesis approaches over stochastic systems have received
significant attention in the past few years, in view of their ability to
provide provably correct controllers for complex logical specifications in an
automated fashion. Examples of complex specifications of interest include
properties expressed as formulae in linear temporal logic (LTL) or as automata
on infinite strings. A general methodology to synthesize controllers for such
properties resorts to symbolic abstractions of the given stochastic systems.
Symbolic models are discrete abstractions of the given concrete systems with
the property that a controller designed on the abstraction can be refined (or
implemented) into a controller on the original system. Although the recent
development of techniques for the construction of symbolic models has been
quite encouraging, the general goal of formal synthesis over stochastic control
systems is by no means solved. A fundamental issue with the existing techniques
is the known "curse of dimensionality," which is due to the need to discretize
state and input sets and that results in an exponential complexity over the
number of state and input variables in the concrete system. In this work we
propose a novel abstraction technique for incrementally stable stochastic
control systems, which does not require state-space discretization but only
input set discretization, and that can be potentially more efficient (and thus
scalable) than existing approaches. We elucidate the effectiveness of the
proposed approach by synthesizing a schedule for the coordination of two
traffic lights under some safety and fairness requirements for a road traffic
model. Further we argue that this 5-dimensional linear stochastic control
system cannot be studied with existing approaches based on state-space
discretization due to the very large number of generated discrete states.Comment: 22 pages, 3 figures. arXiv admin note: text overlap with
arXiv:1407.273
Stochastic stability for a model representing the intake manifold pressure of an automotive engine
The paper presents conditions to assure stochastic stability for a nonlinear model. The proposed model is used to represent the input-output dynamics of the angle of aperture of the throttle valve (input) and the manifold absolute pressure (output) in an automotive spark-ignition engine. The automotive model is second moment stable, as stated by the theoretical result—data collected from real-time experiments supports this finding.Peer ReviewedPostprint (author's final draft
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