13,962 research outputs found
On design of quantized fault detection filters with randomly occurring nonlinearities and mixed time-delays
This paper is concerned with the fault detection problem for a class of discrete-time systems with randomly occurring nonlinearities, mixed stochastic time-delays as well as measurement quantizations. The nonlinearities are assumed to occur in a random way. The mixed time-delays comprise both the multiple discrete time-delays and the infinite distributed delays that occur in a random way as well. A sequence of stochastic variables is introduced to govern the random occurrences of the nonlinearities, discrete time-delays and distributed time-delays, where all the stochastic variables are mutually independent but obey the Bernoulli distribution. The main purpose of this paper is to design a fault detection filter such that, in the presence of measurement quantization, the overall fault detection dynamics is exponentially stable in the mean square and, at the same time, the error between the residual signal and the fault signal is made as small as possible. Sufficient conditions are first established via intensive stochastic analysis for the existence of the desired fault detection filters, and then the explicit expression of the desired filter gains is derived by means of the feasibility of certain matrix inequalities. Also, the optimal performance index for the addressed fault detection problem can be obtained by solving an auxiliary convex optimization problem. A practical example is provided to show the usefulness and effectiveness of the proposed design method
Sampled-Data Kalman Filtering and Multiple Model Adaptive Estimation for Infinite-Dimensional Continuous-Time Systems
Kalman filtering and multiple model adaptive estimation (MMAE) methods have been applied by researchers in several engineering disciplines to a multitude of problems featuring a linear (or mildly nonlinear) model based on finite-dimensional differential (or difference) equations perturbed by random inputs. However, many real-world systems are more naturally modeled using an infinite-dimensional continuous-time linear systems model, such as those most naturally modeled as partial differential equations or time-delayed differential equations along with a possibly infinite-dimensional measurement model. The Kalman filtering technique was extended to encompass infinite-dimensional continuous-time systems with sampled-data measurements and a technique to approximate an infinite-dimensional continuous-time system model with an essentially equivalent finite-dimensional discrete-time model upon which a filtering algorithm could be based was developed. The tools developed during this research were demonstrated using an estimation problem based on a stochastic partial differential equation with an unknown noise environment
Local ensemble transform Kalman filter, a fast non-stationary control law for adaptive optics on ELTs: theoretical aspects and first simulation results
We propose a new algorithm for an adaptive optics system control law, based
on the Linear Quadratic Gaussian approach and a Kalman Filter adaptation with
localizations. It allows to handle non-stationary behaviors, to obtain
performance close to the optimality defined with the residual phase variance
minimization criterion, and to reduce the computational burden with an
intrinsically parallel implementation on the Extremely Large Telescopes (ELTs).Comment: This paper was published in Optics Express and is made available as
an electronic reprint with the permission of OSA. The paper can be found at
the following URL on the OSA website: http://www.opticsinfobase.org/oe/ .
Systematic or multiple reproduction or distribution to multiple locations via
electronic or other means is prohibited and is subject to penalties under la
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On nonlinear H∞ filtering for discrete-time stochastic systems with missing measurements
Copyright [2008] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, the H∞ filtering problem is investigated for a general class of nonlinear discrete-time stochastic systems with missing measurements. The system under study is not only corrupted by state-dependent white noises but also disturbed by exogenous inputs. The measurement output contains randomly missing data that is modeled by a Bernoulli distributed white sequence with a known conditional probability. A filter of very general form is first designed such that the filtering process is stochastically stable and the filtering error satisfies H infin performance constraint for all admissible missing observations and nonzero exogenous disturbances under the zero-initial condition. The existence conditions of the desired filter are described in terms of a second-order nonlinear inequality. Such an inequality can be decoupled into some auxiliary ones that can be solved independently by taking special form of the Lyapunov functionals. As a consequence, a linear time-invariant filter design problem is discussed for the benefit of practical applications, and some simplified conditions are obtained. Finally, two numerical simulation examples are given to illustrate the main results of this paper
Some special solutions to the Hyperbolic NLS equation
The Hyperbolic Nonlinear Schrodinger equation (HypNLS) arises as a model for
the dynamics of three-dimensional narrowband deep water gravity waves. In this
study, the Petviashvili method is exploited to numerically compute bi-periodic
time-harmonic solutions of the HypNLS equation. In physical space they
represent non-localized standing waves. Non-trivial spatial patterns are
revealed and an attempt is made to describe them using symbolic dynamics and
the language of substitutions. Finally, the dynamics of a slightly perturbed
standing wave is numerically investigated by means a highly acccurate Fourier
solver.Comment: 33 pages, 10 figures, 70 references. Other author's papers can be
found at http://www.denys-dutykh.com
Characterization of Model-Based Detectors for CPS Sensor Faults/Attacks
A vector-valued model-based cumulative sum (CUSUM) procedure is proposed for
identifying faulty/falsified sensor measurements. First, given the system
dynamics, we derive tools for tuning the CUSUM procedure in the fault/attack
free case to fulfill a desired detection performance (in terms of false alarm
rate). We use the widely-used chi-squared fault/attack detection procedure as a
benchmark to compare the performance of the CUSUM. In particular, we
characterize the state degradation that a class of attacks can induce to the
system while enforcing that the detectors (CUSUM and chi-squared) do not raise
alarms. In doing so, we find the upper bound of state degradation that is
possible by an undetected attacker. We quantify the advantage of using a
dynamic detector (CUSUM), which leverages the history of the state, over a
static detector (chi-squared) which uses a single measurement at a time.
Simulations of a chemical reactor with heat exchanger are presented to
illustrate the performance of our tools.Comment: Submitted to IEEE Transactions on Control Systems Technolog
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
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