Reliable H∞ control for discrete-time piecewise linear systems with infinite distributed delays

In this paper, the reliable H∞ control problem is investigated for discrete-time piecewise linear systems with time delays and actuator failures. The time delays are assumed to be infinitely distributed in the discrete-time domain, and the possible failure of each actuator is described by a variable varying in a given interval. The aim of the addressed reliable H∞ control problem is to design a controller such that, for the admissible infinite distributed delays and possible actuator failures, the closed-loop system is exponentially stable with a given disturbance attenuation level γ. The controller gain is characterized in terms of the solution to a linear matrix inequality that can be easily solved by using standard software packages. A simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures

A delay-dependent approach to H∞ filtering for stochastic delayed jumping systems with sensor non-linearities

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Taylor & Francis Ltd.In this paper, a delay-dependent approach is developed to deal with the stochastic H∞ filtering problem for a class of It type stochastic time-delay jumping systems subject to both the sensor non-linearities and the exogenous non-linear disturbances. The time delays enter into the system states, the sensor non-linearities and the external non-linear disturbances. The purpose of the addressed filtering problem is to seek an H∞ filter such that, in the simultaneous presence of non-linear disturbances, sensor non-linearity as well as Markovian jumping parameters, the filtering error dynamics for the stochastic time-delay system is stochastically stable with a guaranteed disturbance rejection attenuation level γ. By using It's differential formula and the Lyapunov stability theory, we develop a linear matrix inequality approach to derive sufficient conditions under which the desired filters exist. These conditions are dependent on the length of the time delay. We then characterize the expression of the filter parameters, and use a simulation example to demonstrate the effectiveness of the proposed results.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Nuffield Foundation of the U.K.under Grant NAL/00630/G, and the Alexander von Humboldt Foundation of Germany

H∞ filtering for nonlinear discrete-time stochastic systems with randomly varying sensor delays

This is the post print version of the article. The official published version can be obained from the link - Copyright 2009 Elsevier LtdThis paper is concerned with the H∞ filtering problem for a general class of nonlinear discrete-time stochastic systems with randomly varying sensor delays, where the delayed sensor measurement is governed by a stochastic variable satisfying the Bernoulli random binary distribution law. In terms of the Hamilton–Jacobi–Isaacs inequalities, preliminary results are first obtained that ensure the addressed system to possess an l2-gain less than a given positive scalar γ. Next, a sufficient condition is established under which the filtering process is asymptotically stable in the mean square and the filtering error satisfies the H∞ performance constraint for all nonzero exogenous disturbances under the zero-initial condition. Such a sufficient condition is then decoupled into four inequalities for the purpose of easy implementation. Furthermore, it is shown that our main results can be readily specialized to the case of linear stochastic systems. Finally, a numerical simulation example is used to demonstrate the effectiveness of the results derived.This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Associate Editor James Lam under the direction of Editor Ian R. Petersen. This work was supported by the Shanghai Natural Science Foundation under Grant 07ZR14002, 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 robust extended H-infinity filtering approach to multi-robot cooperative localization in dynamic indoor environments

Multi-robot cooperative localization serves as an essential task for a team of mobile robots to work within an unknown environment. Based on the real-time laser scanning data interaction, a robust approach is proposed to obtain optimal multi-robot relative observations using the Metric-based Iterative Closest Point (MbICP) algorithm, which makes it possible to utilize the surrounding environment information directly instead of placing a localization-mark on the robots. To meet the demand of dealing with the inherent non-linearities existing in the multi-robot kinematic models and the relative observations, a robust extended H∞ filtering (REHF) approach is developed for the multi-robot cooperative localization system, which could handle non-Gaussian process and measurement noises with respect to robot navigation in unknown dynamic scenes. Compared with the conventional multi-robot localization system using extended Kalman filtering (EKF) approach, the proposed filtering algorithm is capable of providing superior performance in a dynamic indoor environment with outlier disturbances. Both numerical experiments and experiments conducted for the Pioneer3-DX robots show that the proposed localization scheme is effective in improving both the accuracy and reliability of the performance within a complex environment.This work was supported inpart by the National Natural Science Foundation of China under grants 61075094, 61035005 and 61134009

Robust filtering with stochastic nonlinearities and multiple missing measurements

This is the post print version of the article. The official published version can be obtained from the link - Copyright 2009 Elsevier LtdThis paper is concerned with the filtering problem for a class of discrete-time uncertain stochastic nonlinear time-delay systems with both the probabilistic missing measurements and external stochastic disturbances. The measurement missing phenomenon is assumed to occur in a random way, and the missing probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution over the interval . Such a probabilistic distribution could be any commonly used discrete distribution over the interval . The multiplicative stochastic disturbances are in the form of a scalar Gaussian white noise with unit variance. The purpose of the addressed filtering problem is to design a filter such that, for the admissible random measurement missing, stochastic disturbances, norm-bounded uncertainties as well as stochastic nonlinearities, the error dynamics of the filtering process is exponentially mean-square stable. By using the linear matrix inequality (LMI) method, sufficient conditions are established that ensure the exponential mean-square stability of the filtering error, and then the filter parameters are characterized by the solution to a set of LMIs. Illustrative examples are exploited to show the effectiveness of the proposed design procedures.This work was supported in part by the Shanghai Natural Science Foundation under Grant 07ZR14002, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, an International Joint Project sponsored by the Royal Society of the UK, the Nuffield Foundation of the UK under Grant NAL/00630/G and the Alexander von Humboldt Foundation of Germany

Fast Color-guided Depth Denoising for RGB-D Images by Graph Filtering

Depth images captured by off-the-shelf RGB-D cameras suffer from much stronger noise than color images. In this paper, we propose a method to denoise the depth images in RGB-D images by color-guided graph filtering. Our iterative method contains two components: color-guided similarity graph construction, and graph filtering on the depth signal. Implemented in graph vertex domain, filtering is accelerated as computation only occurs among neighboring vertices. Experimental results show that our method outperforms state-of-art depth image denoising methods significantly both on quality and efficiency.Comment: 5 pages, 4 figure

A note on control of a class of discrete-time stochastic systems with distributed delays and nonlinear disturbances

The official published version of this article can be found at the link below.This paper is concerned with the state feedback control problem for a class of discrete-time stochastic systems involving sector nonlinearities and mixed time-delays. The mixed time-delays comprise both discrete and distributed delays, and the sector nonlinearities appear in the system states and all delayed states. The distributed time-delays in the discrete-time domain are first defined and then a special matrix inequality is developed to handle the distributed time-delays within an algebraic framework. An effective linear matrix inequality (LMI) approach is proposed to design the state feedback controllers such that, for all admissible nonlinearities and time-delays, the overall closed-loop system is asymptotically stable in the mean square sense. Sufficient conditions are established for the nonlinear stochastic time-delay systems to be asymptotically stable in the mean square sense, and then the explicit expression of the desired controller gains is derived. A numerical example is provided to show the usefulness and effectiveness of the proposed design method.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., the National Natural Science Foundation of China under Grants 60774073 and 60974030, the National 973 Program of China under Grant 2009CB320600, and the Alexander von Humboldt Foundation of Germany

Computational Study on the Microscopic Adsorption Characteristics of Linear Alkylbenzene Sulfonates with Different Chain Lengths on Anthracite Surface

In order to explore the influence of different lengths of hydrophobic carbon chains on the diffusion characteristics of surfactants on the surface of anthracite, six linear alkyl benzene sulfonates with different hydrophobic carbon chain lengths were selected (mC, m = 8, 10, 12, 14, 16, 18; m represents the numbers of carbon atoms in the hydrophobic carbon chain), and molecular dynamics (MD) simulations were adopted. Models of surfactant-anthracite, surfactant-graphite layer, and water-surfactant-anthracite were constructed. After analyzing a series of properties such as adsorption energy, diffusion coefficient, radial distribution function (RDF), and hydrophobic tail order parameters, it was found that 12C had the highest adsorption strength on the surface of anthracite; the reason was that 12C had the highest degree of aggregation near the oxygen-containing functional groups on the surface of anthracite. Further studies had found that the hydrophobic tail chain of 12C had the strongest isotropy. The study fills the gap in the systematic study of the diffusion characteristics of linear alkylbenzene sulfonates (LAS) with different chain lengths on the surface of anthracite, enriches and develops the basic theory of coal wettability, and also provides technical ideas for the design of new surfactants and new dust suppression agents

Microstructure and mechanical properties of wire and arc additive manufactured thin wall with low-temperature transformation

Low-temperature transformation (LTT) welding wire was initially developed to mitigate residual stress in the weld. It could also be used for internal stress optimization in Wire and Arc Additive Manufacturing (WAAM) process. In this study, a 26 layers LTT wall sample fabricated by using the WAAM technique was investigated. The microstructure of the LTT deposited wall includes elongated cellular martensite and reticular residual austenite. With the accumulation of deposition height, the prior austenite grain size increases, and the volume fraction of residual austenite and the density of dislocations in martensite decreases. According to the model of martensite transformation kinetics, the original austenite grain size is the main reason that affects the austenite fraction. In addition, the presence of a thermal cycle leads to the refinement of the martensitic microstructure and the increase in the boundary density, as well as the elimination of the sub-stable austenitic phase resulting in higher tensile properties in the middle samples than in the top ones. From the current work, it is clear that the unique thermal cycle treatment of WAAM is beneficial in improving the performance of LTT materials.</p