2,661 research outputs found
A Decoding Approach to Fault Tolerant Control of Linear Systems with Quantized Disturbance Input
The aim of this paper is to propose an alternative method to solve a Fault
Tolerant Control problem. The model is a linear system affected by a
disturbance term: this represents a large class of technological faulty
processes. The goal is to make the system able to tolerate the undesired
perturbation, i.e., to remove or at least reduce its negative effects; such a
task is performed in three steps: the detection of the fault, its
identification and the consequent process recovery. When the disturbance
function is known to be \emph{quantized} over a finite number of levels, the
detection can be successfully executed by a recursive \emph{decoding}
algorithm, arising from Information and Coding Theory and suitably adapted to
the control framework. This technique is analyzed and tested in a flight
control issue; both theoretical considerations and simulations are reported
Recent advances on filtering and control for nonlinear stochastic complex systems with incomplete information: A survey
This Article is provided by the Brunel Open Access Publishing Fund - Copyright @ 2012 Hindawi PublishingSome recent advances on the filtering and control problems for nonlinear stochastic complex systems with incomplete information are surveyed. The incomplete information under consideration mainly includes missing measurements, randomly varying sensor delays, signal quantization, sensor saturations, and signal sampling. With such incomplete information, the developments on various filtering and control issues are reviewed in great detail. In particular, the addressed nonlinear stochastic complex systems are so comprehensive that they include conventional nonlinear stochastic systems, different kinds of complex networks, and a large class of sensor networks. The corresponding filtering and control technologies for such nonlinear stochastic complex systems are then discussed. Subsequently, some latest results on the filtering and control problems for the complex systems with incomplete information are given. Finally, conclusions are drawn and several possible future research directions are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grant nos. 61134009, 61104125, 61028008, 61174136, 60974030, and 61074129, the Qing Lan Project of Jiangsu Province of China, the Project sponsored by SRF for ROCS of SEM of China, the Engineering and Physical Sciences Research Council EPSRC of the UK under Grant GR/S27658/01, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
A unified framework for solving a general class of conditional and robust set-membership estimation problems
In this paper we present a unified framework for solving a general class of
problems arising in the context of set-membership estimation/identification
theory. More precisely, the paper aims at providing an original approach for
the computation of optimal conditional and robust projection estimates in a
nonlinear estimation setting where the operator relating the data and the
parameter to be estimated is assumed to be a generic multivariate polynomial
function and the uncertainties affecting the data are assumed to belong to
semialgebraic sets. By noticing that the computation of both the conditional
and the robust projection optimal estimators requires the solution to min-max
optimization problems that share the same structure, we propose a unified
two-stage approach based on semidefinite-relaxation techniques for solving such
estimation problems. The key idea of the proposed procedure is to recognize
that the optimal functional of the inner optimization problems can be
approximated to any desired precision by a multivariate polynomial function by
suitably exploiting recently proposed results in the field of parametric
optimization. Two simulation examples are reported to show the effectiveness of
the proposed approach.Comment: Accpeted for publication in the IEEE Transactions on Automatic
Control (2014
Guiding-center dynamics of vortex dipoles in Bose-Einstein condensates
A quantized vortex dipole is the simplest vortex molecule, comprising two
counter-circulating vortex lines in a superfluid. Although vortex dipoles are
endemic in two-dimensional superfluids, the precise details of their dynamics
have remained largely unexplored. We present here several striking observations
of vortex dipoles in dilute-gas Bose-Einstein condensates, and develop a
vortex-particle model that generates vortex line trajectories that are in good
agreement with the experimental data. Interestingly, these diverse trajectories
exhibit essentially identical quasi-periodic behavior, in which the vortex
lines undergo stable epicyclic orbits.Comment: 4 pages, 2 figure
Fuzzy-logic-based control, filtering, and fault detection for networked systems: A Survey
This paper is concerned with the overview of the recent progress in fuzzy-logic-based filtering, control, and fault detection problems. First, the network technologies are introduced, the networked control systems are categorized from the aspects of fieldbuses and industrial Ethernets, the necessity of utilizing the fuzzy logic is justified, and the network-induced phenomena are discussed. Then, the fuzzy logic control strategies are reviewed in great detail. Special attention is given to the thorough examination on the latest results for fuzzy PID control, fuzzy adaptive control, and fuzzy tracking control problems. Furthermore, recent advances
on the fuzzy-logic-based filtering and fault detection problems are reviewed. Finally, conclusions are given and some possible future research directions are pointed out, for example, topics on two-dimensional networked systems, wireless networked control systems, Quality-of-Service (QoS) of networked systems, and fuzzy access control in open networked systems.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301,
61374039, 61473163, and 61374127, the Hujiang Foundation of China under Grants C14002 andD15009, the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Recent advances on recursive filtering and sliding mode design for networked nonlinear stochastic systems: A survey
Copyright © 2013 Jun Hu 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.Some recent advances on the recursive filtering and sliding mode design problems for nonlinear stochastic systems with network-induced phenomena are surveyed. The network-induced phenomena under consideration mainly include missing measurements, fading measurements, signal quantization, probabilistic sensor delays, sensor saturations, randomly occurring nonlinearities, and randomly occurring uncertainties. With respect to these network-induced phenomena, the developments on filtering and sliding mode design problems are systematically reviewed. In particular, concerning the network-induced phenomena, some recent results on the recursive filtering for time-varying nonlinear stochastic systems and sliding mode design for time-invariant nonlinear stochastic systems are given, respectively. Finally, conclusions are proposed and some potential future research works are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grant nos. 61134009, 61329301, 61333012, 61374127 and 11301118, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant no. GR/S27658/01, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Cram\'er-Rao Bounds for Polynomial Signal Estimation using Sensors with AR(1) Drift
We seek to characterize the estimation performance of a sensor network where
the individual sensors exhibit the phenomenon of drift, i.e., a gradual change
of the bias. Though estimation in the presence of random errors has been
extensively studied in the literature, the loss of estimation performance due
to systematic errors like drift have rarely been looked into. In this paper, we
derive closed-form Fisher Information matrix and subsequently Cram\'er-Rao
bounds (upto reasonable approximation) for the estimation accuracy of
drift-corrupted signals. We assume a polynomial time-series as the
representative signal and an autoregressive process model for the drift. When
the Markov parameter for drift \rho<1, we show that the first-order effect of
drift is asymptotically equivalent to scaling the measurement noise by an
appropriate factor. For \rho=1, i.e., when the drift is non-stationary, we show
that the constant part of a signal can only be estimated inconsistently
(non-zero asymptotic variance). Practical usage of the results are demonstrated
through the analysis of 1) networks with multiple sensors and 2) bandwidth
limited networks communicating only quantized observations.Comment: 14 pages, 6 figures, This paper will appear in the Oct/Nov 2012 issue
of IEEE Transactions on Signal Processin
Observer-based tuning of two-inertia servo-drive systems with integrated SAW torque transducers
This paper proposes controller design and tuning
methodologies that facilitate the rejection of periodic load-side disturbances applied to a torsional mechanical system while simultaneously compensating for the observer’s inherent phase delay. This facilitates the use of lower-bandwidth practically realizable disturbance observers. The merits of implementing full- and reduced-order observers are investigated, with the latter being implemented with a new low-cost servo-machine-integrated highband width
torque-sensing device based on surface acoustic wave
(SAW) technology. Specifically, the authors’ previous work based on proportional–integral–derivative (PID) and resonance ratio control (RRC) controllers (IEEE Trans. Ind. Electron., vol. 53, no. 4, pp. 1226–1237, Aug. 2006) is augmented with observer disturbance feedback. It is shown that higher-bandwidth disturbance observers are required to maximize disturbance attenuation over the low-frequency band (as well as the desired rejection frequency), thereby attenuating a wide range of possible frequencies. In such cases, therefore, it is shown that the RRC controller is
the preferred solution since it can employ significantly higher observer bandwidth, when compared to PID counterparts, by virtue of reduced noise sensitivity. Furthermore, it is demonstrated that the prototype servo-machine-integrated 20-N · mSAWtorque transducer is not unduly affected by machine-generated electromagnetic
noise and exhibits similar dynamic behavior as a
conventional instrument inline torque transducer
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