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

Objectivity in molecular dynamics

In classical Continuum Mechanics, Principle of Objectivity requires that balance laws and constitutive equations must be form-invariant with respect to rigid motions of the spatial frame of reference. Any tensorial quantity is said to be objective if it obeys the appropriate tensor transformation law. Quantities such as temperature and stress tensor are known to be objective. In Molecular Dynamics (MD) simulation, which is a prevalent numerical method in nanoscience on atomistic basis, Principle of Objectivity was rarely discussed. This research explores the objectivity issue in the classical MD by examining the governing equation and constitutive equation. It can be shown that the interatomic potential and the corresponding interatomic force are objective because they are determined by relative atomic positions, which are objective. On the other hand, velocity and relative velocity are not objective. As a consequence, quantities such as temperature and Virial stress that are calculated based on apparent atomic velocities are not objective. Therefore, multiphysics body forces generated by these nonobjective quantities are not objective either. This becomes problematic when the system or subsystem is described in a noninertial reference frame, i.e., the reference frame undergoes acceleration or rotation. To resolve this deficiency, this research proposes the theory of Objectivity Incorporated MD. With the adoption of an objective form of velocity, the objectivity of temperature and Virial stress are restored. The theory also requires all kinds of body forces to be objective so that the constitutive equation well satisfies the Principle of Objectivity. The theory further supplements the governing equation with fictitious force, which accounts for the motion of reference frame, so that MD simulation can be extended to noninertial reference frame. It is considered that the application of Principle of Objectivity on MD will provide more power and credibility to the simulations of complex systems

Robust finite-horizon filtering for stochastic systems with missing measurements

Copyright [2005] 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 letter, we consider the robust finite-horizon filtering problem for a class of discrete time-varying systems with missing measurements and norm-bounded parameter uncertainties. The missing measurements are described by a binary switching sequence satisfying a conditional probability distribution. An upper bound for the state estimation error variance is first derived for all possible missing observations and all admissible parameter uncertainties. Then, a robust filter is designed, guaranteeing that the variance of the state estimation error is not more than the prescribed upper bound. It is shown that the desired filter can be obtained in terms of the solutions to two discrete Riccati difference equations, which are of a form suitable for recursive computation in online applications. A simulation example is presented to show the effectiveness of the proposed approach by comparing to the traditional Kalman filtering method

Pinning control of fractional-order weighted complex networks

In this paper, we consider the pinning control problem of fractional-order weighted complex dynamical networks. The well-studied integer-order complex networks are the special cases of the fractional-order ones. The network model considered can represent both directed and undirected weighted networks. First, based on the eigenvalue analysis and fractional-order stability theory, some local stability properties of such pinned fractional-order networks are derived and the valid stability regions are estimated. A surprising finding is that the fractional-order complex networks can stabilize itself by reducing the fractional-order q without pinning any node. Second, numerical algorithms for fractional-order complex networks are introduced in detail. Finally, numerical simulations in scale-free complex networks are provided to show that the smaller fractional-order q, the larger control gain matrix D, the larger tunable weight parameter , the larger overall coupling strength c, the more capacity that the pinning scheme may possess to enhance the control performance of fractional-order complex networks

Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case

The official published version of the article can be found at the link below.This paper is concerned with a new distributed H∞-consensus filtering problem over a finite-horizon for sensor networks with multiple missing measurements. The so-called H∞-consensus performance requirement is defined to quantify bounded consensus regarding the filtering errors (agreements) over a finite-horizon. A set of random variables are utilized to model the probabilistic information missing phenomena occurring in the channels from the system to the sensors. A sufficient condition is first established in terms of a set of difference linear matrix inequalities (DLMIs) under which the expected H∞-consensus performance constraint is guaranteed. Given the measurements and estimates of the system state and its neighbors, the filter parameters are then explicitly parameterized by means of the solutions to a certain set of DLMIs that can be computed recursively. Subsequently, two kinds of robust distributed H∞-consensus filters are designed for the system with norm-bounded uncertainties and polytopic uncertainties. Finally, two numerical simulation examples are used to demonstrate the effectiveness of the proposed distributed filters design scheme.This work was supported in part by 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

Multiobjective synchronization of coupled systems

Copyright @ 2011 American Institute of PhysicsSynchronization of coupled chaotic systems has been a subject of great interest and importance, in theory but also various fields of application, such as secure communication and neuroscience. Recently, based on stability theory, synchronization of coupled chaotic systems by designing appropriate coupling has been widely investigated. However, almost all the available results have been focusing on ensuring the synchronization of coupled chaotic systems with as small coupling strengths as possible. In this contribution, we study multiobjective synchronization of coupled chaotic systems by considering two objectives in parallel, i. e., minimizing optimization of coupling strength and convergence speed. The coupling form and coupling strength are optimized by an improved multiobjective evolutionary approach. The constraints on the coupling form are also investigated by formulating the problem into a multiobjective constraint problem. We find that the proposed evolutionary method can outperform conventional adaptive strategy in several respects. The results presented in this paper can be extended into nonlinear time-series analysis, synchronization of complex networks and have various applications

Almost sure H∞ filtering for nonlinear hybrid stochastic systems with mode-dependent interval delays

In this paper, the problem of almost sure H∞ filtering is studied for a class of nonlinear hybrid stochastic systems. In the system under investigation, Markovian jumping parameters, mode-dependent interval delays, nonzero exogenous disturbances as well as white noises are simultaneously taken into consideration to better model the real-world systems. Intensive stochastic analysis is carried out to obtain sufficient conditions for ensuring the almost surely exponential stability and the prescribed H∞ performance for the overall filtering error dynamics. Furthermore, the obtained results are applied to two classes of special hybrid stochastic systems with mode-dependent interval delays, where the desired filter gain is obtained in terms of the solutions to a set of linear matrix inequalities. Finally, two numerical examples are provided to show the effectiveness of the proposed filter design scheme.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009 and 61329301, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

Observer-based networked control for continuous-time systems with random sensor delays

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 networked control system design for continuous-time systems with random measurement, where the measurement channel is assumed to subject to random sensor delay. A design scheme for the observer-based output feedback controller is proposed to render the closed-loop networked system exponentially mean-square stable with H∞ performance requirement. The technique employed is based on appropriate delay systems approach combined with a matrix variable decoupling technique. The design method is fulfilled through solving linear matrix inequalities. A numerical example is used to verify the effectiveness and the merits of the present results.This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Associate Editor George Yin under the direction of Editor Ian R. Petersen. This work was supported in part by the Royal Society of the UK, the National Natural Science Foundation of China (60774047, 60674055) and the Taishan Scholar Programs Foundation of Shandong Province, China

Robust fault detection for networked systems with communication delay and data missing

n this paper, the robust fault detection problem is investigated for a class of discrete-time networked systems with unknown input and multiple state delays. A novel measurement model is utilized to represent both the random measurement delays and the stochastic data missing phenomenon, which typically result from the limited capacity of the communication networks. The network status is assumed to vary in a Markovian fashion and its transition probability matrix is uncertain but resides in a known convex set of a polytopic type. The main purpose of this paper is to design a robust fault detection filter such that, for all unknown inputs, possible parameter uncertainties and incomplete measurements, the error between the residual signal and the fault signal is made as small as possible. By casting the addressed robust fault detection problem into an auxiliary robust H∞ filtering problem of a certain Markovian jumping system, a sufficient condition for the existence of the desired robust fault detection filter is established in terms of linear matrix inequalities. A numerical example is provided to illustrate the effectiveness and applicability of the proposed technique

Robust variance-constrained H∞ control for stochastic systems with multiplicative noises

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Elsevier Ltd.In this paper, the robust variance-constrained H∞ control problem is considered for uncertain stochastic systems with multiplicative noises. The norm-bounded parametric uncertainties enter into both the system and output matrices. The purpose of the problem is to design a state feedback controller such that, for all admissible parameter uncertainties, (1) the closed-loop system is exponentially mean-square quadratically stable; (2) the individual steady-state variance satisfies given upper bound constraints; and (3) the prescribed noise attenuation level is guaranteed in an H∞ sense with respect to the additive noise disturbances. A general framework is established to solve the addressed multiobjective problem by using a linear matrix inequality (LMI) approach, where the required stability, the H∞ characterization and variance constraints are all easily enforced. Within such a framework, two additional optimization problems are formulated: one is to optimize the H∞ performance, and the other is to minimize the weighted sum of the system state variances. A numerical example is provided to illustrate the effectiveness of the proposed design algorithm.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Nuffield Foundation of the UK under Grant NAL/00630/G, and the Alexander von Humboldt Foundation of Germany