stability of singularly perturbed switched systems with time delay and impulsive effects abstract this paper studies the stability properties of singularly perturbed switched systems with time delay and impulsive effects such systems are assumed to consist of both unstable and stable subsystems by using the multiple lyapunov functions technique and the dwell time approach some stability criteria are established our results show that impulses do contribute in order to obtain stability properties even when the system consists of only unstable subsystems numerical examples are presented to verify our theoretical results

delay independent stability analysis of linear time delay systems based on frequency discretization this paper studies strong delay independent stability of linear time invariant systems it is known that delay independent stability of time delay systems is equivalent to some frequency dependent linear matrix inequalities to reduce or eliminate conservatism of stability criteria the frequency domain is discretized into several sub intervals and piecewise constant lyapunov matrices are employed to analyze the frequency dependent stability condition applying the generalized kalman yakubovich popov lemma new necessary and sufficient criteria are then obtained for strong delay independent stability of systems with a single delay the effectiveness of the proposed method is illustrated by a numerical example

on stabilization of bilinear uncertain time delay stochastic systems with markovian jumping parameters in this paper we investigate the stochastic stabilization problem for a class of bilinear continuous time delay uncertain systems with markovian jumping parameters specifically the stochastic bilinear jump system under study involves unknown state time delay parameter uncertainties and unknown nonlinear deterministic disturbances the jumping parameters considered here form a continuous time discrete state homogeneous markov process the whole system may be regarded as a stochastic bilinear hybrid system that includes both time evolving and event driven mechanisms our attention is focused on the design of a robust state feedback controller such that for all admissible uncertainties as well as nonlinear disturbances the closed loop system is stochastically exponentially stable in the mean square independent of the time delay sufficient conditions are established to guarantee the existence of desired robust controllers which are given in terms of the solutions to a set of either linear matrix inequalities lmis or coupled quadratic matrix inequalities the developed theory is illustrated by numerical simulation

analysis and design of impulsive control systems some sufficient conditions for asymptotic stability of impulsive control systems with impulses at fixed times have recently been presented in this paper we derive some less conservative conditions for asymptotic stability of such impulsive control systems and the results are used to design impulsive control for a class of nonlinear systems the class of nonlinear systems considered is also extended

dissipativity analysis for singular systems with time varying delays this paper is concerned with the dissipativity analysis problem for singular systems with time varying delays a delay dependent criterion is established to guarantee the dissipativity of the underlying systems using the delay partitioning technique all the results given in this paper are not only dependent upon the time delay but also dependent upon the number of delay partitions the effectiveness and the reduced conservatism of the derived results are demonstrated by two illustrative examples

robust stability of a class of hybrid nonlinear systems we analyze the discrete behavior to identify all kinds of cycles of hybrid nonlinear systems and then study the continuous behavior along each kind of cycle based on these analysis we construct some continuous functions to bound lyapunov functions along all subsystems and identify a subsequence of time points where the lyapunov functions are non increasing we use these results to derive some new sufficient conditions for the robust stability of a class of hybrid nonlinear systems with polytopic uncertainties these conditions do not require the lyapunov functions to be non increasing along each subsystem nor the whole sequence of the switching furthermore they do not require the knowledge of continuous trajectory

delay independent minimum dwell time for exponential stability of uncertain switched delay systems in this technical note the problem of delay independent minimum dwell time for exponential stability of uncertain switched delay systems is considered piecewise time varying lyapunov functionals functions which are decreasing at switching times by construction are introduced to investigate exponential stability of switched delay systems with constant or time varying delays this type of delicately constructed lyapunov functionals functions can efficiently eliminate the jump phenomena of adjacent lyapunov functionals functions at switching times without imposing any restriction on the sizes of time delays by applying this type of lyapunov functionals functions it is shown that if each subsystem is delay independently exponentially stable then under some conditions there exists a delay independent minimum dwell time in the sense that the switched delay system with such minimum dwell time is exponentially stable irrespective of the sizes of the time delays two numerical examples are provided to demonstrate the efficiency of the proposed approach

fuzzy impulsive control for uncertain nonlinear systems with guaranteed cost in this paper a guaranteed cost fuzzy impulsive control gcfic problem is addressed for uncertain continuous time nonlinear systems which can be represented by the takagi sugeno t s fuzzy model with parametric uncertainties based on the t s fuzzy model a novel time varying lyapunov function is initially constructed to derive the existence condition of guaranteed cost fuzzy impulsive controllers which cannot only exponentially stabilize the uncertain fuzzy system but also provide an upper bound on the quadratic cost function then two procedures for designing suboptimal guaranteed cost fuzzy impulsive controllers are given in the sense of minimizing an upper bound of the cost function one casts the controller design into a parameter dependent linear matrix inequality lmi optimization problem and the other casts the controller design into a sequential minimization problem subject to lmi constraints by using the cone complementary linearization ccl algorithm finally an example is presented to illustrate the effectiveness of the proposed method

on asymptotic normality and variance estimation for nondifferentiable survey estimators survey estimators of population quantities such as distribution functions and quantiles contain nondifferentiable functions of estimated quantities the theoretical properties of such estimators are substantially more complicated to derive than those of differentiable estimators in this article we provide a unified framework for obtaining the asymptotic design based properties of two common types of nondifferentiable estimators estimators of the first type have an explicit expression while those of the second are defined only as the solution to estimating equations we propose both analytical and replication based design consistent variance estimators for both cases based on kernel regression the practical behaviour of the variance estimators is demonstrated in a simulation experiment

multisynchronization of coupled heterogeneous genetic oscillator networks via partial impulsive control this paper focuses on the collective dynamics of multisynchronization among heterogeneous genetic oscillators under a partial impulsive control strategy the coupled nonidentical genetic oscillators are modeled by differential equations with uncertainties the definition of multisynchronization is proposed to describe some more general synchronization behaviors in the real considering that each genetic oscillator consists of a large number of biochemical molecules we design a more manageable impulsive strategy for dynamic networks to achieve multisynchronization not all the molecules but only a small fraction of them in each genetic oscillator are controlled at each impulsive instant theoretical analysis of multisynchronization is carried out by the control theory approach and a sufficient condition of partial impulsive controller for multisynchronization with given error bounds is established at last numerical simulations are exploited to demonstrate the effectiveness of our results

on impulsive control of a periodically forced chaotic pendulum system we consider impulsive control of a periodically forced pendulum system which has rich chaos and bifurcation phenomena a new impulsive control method for chaos suppression of this pendulum system is developed some simple sufficient conditions for driving the chaotic state to its zero equilibrium are presented and some criteria for eventually exponentially asymptotical stability are established this work provides a rigorous theoretical analysis to support some early experimental observations on controlling chaos in the periodically forced pendulum system

optimum calibration points estimating distribution functions the calibration method has been widely discussed in the recent literature on survey sampling and calibration estimators are routinely computed by many survey organizations the calibration technique was introduced in 12 to estimate linear parameters as mean or total recently some authors have applied the calibration technique to estimate the finite distribution function and the quantiles the computationally simpler method in 14 is built by means of constraints that require the use of a fixed value t 0 the precision of the resulting calibration estimator changes with the selected point t 0 in the present paper we study the problem of determining the optimal value t 0 that gives the best estimation under simple random sampling without replacement a limited simulation study shows that the improvement of this optimal calibrated estimator over possible alternatives can be substantial

controllability and observability for a class of controlled switching impulsive systems in this note we study the controllability and observability problem for a class of controlled switching impulsive systems by proposing several formula of variation of parameters for this type of time varying systems and employing the characteristic polynomial theory of matrix we establish necessary and sufficient conditions for controllability and controlled observability with respect to a given switching time sequence specializing the obtained results to the case of time invariant linear switching impulsive systems we derive some simple algebraic criteria which include the results reported in the literature for time invariant linear switching systems linear impulsive systems and classical linear systems one example is worked out for illustration

two dimensional dissipative control and filtering for roesser model this paper investigates the problems of two dimensional 2 d dissipative control and filtering for a linear discrete time roesser model first a novel sufficient condition is proposed such that the discrete time roesser system is asymptotically stable and 2 d q s r hbox alpha dissipative special cases such as 2 d passivity performance and 2 d h infty performance and feedback interconnected systems are also discussed based on this condition new 2 d q s r hbox alpha dissipative state feedback and output feedback control problems are defined and solved for a discrete time roesser model the design problems of 2 d q s r hbox alpha dissipative filters of observer form and general form are also considered using a linear matrix inequality lmi approach two examples are given to illustrate the effectiveness and potential of the proposed design techniques

stability of discrete time delayed impulsive linear systems with application to multi tracking this paper studies the stability issue for discrete time delayed impulsive systems ddis the ddis model is formulated from a discrete time delayed system with impulses by using the matrix spectrum theory the estimates of solution with growth exponent are derived for delayed difference inequalities based on these results two types of criteria on exponential stability with an estimated convergence rate have been established for ddis the first type investigates the effect of destabilising impulses while the second is for the case in which the impulses stabilise the unstable discrete time delayed systems as the application the stability results are used to solve the multi tracking issue for discrete time dynamical networks by mixed impulsive networked control minc in which the impulsive control signals are transmitted via a communication network the effect of data dropout of impulsive control signals is also investigated and the maximal allowable dropout rate is estimated for the designed minc

robust reliable passive control of uncertain stochastic switched time delay systems this paper investigates the problem of robust reliable passive control for a class of uncertain stochastic switched time delay systems with actuator failures the multiple lyapunov functions mlfs technique is exploited to derive a delay dependent sufficient condition for the stochastic switched time delay systems to be passive and exponentially stable under a state based switching law moreover the proposed approach is extended to investigate stochastic switched systems with structured uncertainties finally two numerical examples are presented to illustrate the effectiveness of the proposed method

bias robust estimation in finite populations using nonparametric calibration a standard problem in sample survey inference is that of predicting the finite population total h of a function h y of a random variable y the model based approach to this problem first defines a working model for y and then predicts h by estimating its expectation under conditional on the sample values of y this approach leads to biased predictions if is incorrect we explore an automatic solution to this misspecification bias that uses nonparametric regression to define a robust but inefficient predictor of h and then calibrates this predictor for its bias under an application to prediction of the finite population distribution function of a population of australian beef farms is presented

inference of noisy nonlinear differential equation models for gene regulatory networks using genetic programming and kalman filtering a key issue in genomic signal processing is the inference of gene regulatory networks these are used both to understand the role of biological regulation in phenotypic determination and to derive therapeutic strategies for genetic based diseases in this paper gene regulatory networks are inferred via evolutionary modeling based on time series microarray measurements a nonlinear differential equation model is adopted it includes random noise parameters for intrinsic noise arising from stochasticity in transcription and translation and for external noise arising from factors such as the amount of rna polymerase levels of regulatory proteins and the effects of mrna and protein degradation an iterative algorithm is proposed for model identification genetic programming is applied to identify the structure of the model and kalman filtering is used to estimate the parameters in each iteration both standard and robust kalman filtering are considered the effectiveness of the proposed scheme is demonstrated by using synthetic data and by using microarray measurements pertaining to yeast protein synthesis

a new estimator for the finite population distribution function summary in this paper we propose a new estimator for the finite population distribution function when there is auxiliary information available about the population the new estimator has a smaller asymptotic mean squared error than two leading estimators in the literature in fact it is in an optimised form in terms of mean squared error results are reported for simulation studies on real and artificial populations

sliding mode variable structure control for parameter uncertain stochastic systems with time varying delay in this paper the variable structure control problem for a class uncertain of stochastic system with time varying delay is investigated firstly a new concept of the subordinated reachability of the sliding motion is introduced to approach approximately the specified sliding surface the variable structure control law is then proposed to ensure that the sliding motion is subordinated reachable furthermore a sufficient condition for mean square asymptotical stability of the sliding motion is given finally a numerical example is presented to demonstrate the effectiveness of the obtained results

technical communique lmi based robust h control of uncertain linear jump systems with time delays this paper examines the robust mean square stabilization and robust h control problem for a class of linear systems the systems under consideration involve time delays parameter uncertainties and jumping parameters which may be seen as for example failures that occur in the systems at certain probabilities the uncertain parameters are assumed to be time varying and satisfy boundness conditions a systematic approach via linear matrix inequalities lmi is proposed to solve the problem of concern sufficient conditions for robust mean square stabilization and robust h control are given in the form of lmi and the control law is computed using standard lmi techniques

sensitivity penalization based robust state estimation for uncertain linear systems this technical note deals with robust state estimation when parametric uncertainties nonlinearly affect a plant state space model based on a simultaneous minimization of nominal estimation errors and their sensitivities an analytic solution is derived for the optimal estimator which can be recursively realized this estimator has a form similar to the robust estimator of and its computational complexity is comparable to the kalman filter under certain conditions this robust estimator is proved to converge to a stable system its estimation errors have a bounded covariance matrix and the estimate is asymptotically unbiased numerical simulations show that the obtained estimator has nice estimation performances

on estimating distribution functions and quantiles from survey data using auxiliary information summary ratio and difference estimators of a population distribution function under a general sampling design are obtained using auxiliary population information the relative mean errors and relative mean square errors of these estimators and a model based estimator of chambers dunstan 1986 are compared through a simulation study the advantages of the design based estimators over the model based estimator under model misspecifications especially for large samples are demonstrated ratio and difference estimators of a population quantile are also studied

robust reliable stabilization of stochastic switched nonlinear systems under asynchronous switching this paper is concerned with the problem of robust reliable control for a class of uncertain stochastic switched nonlinear systems under asynchronous switching where the switching instants of the controller experience delays with respect to those of the system a design scheme for the reliable controller is proposed to guarantee almost surely exponential stability for stochastic switched systems with actuator failures and the dwell time approach is utilized for the stability analysis then the approach is extended to take into account stochastic switched system with lipschitz nonlinearities and structured uncertainties finally a numerical example is employed to verify the proposed method

structure identification for gene regulatory networks via linearization and robust state estimation abstract inferring causal relationships among cellular components is one of the fundamental problems in understanding biological behaviours the well known extended kalman filter ekf has been proved to be a useful tool in simultaneously estimating both structure and actual gene expression levels of a gene regulatory network grn first order approximations however unavoidably result in modelling errors but the ekf based method does not take either unmodelled dynamics or parametric uncertainties into account which makes its estimation performances not very satisfactory to overcome these problems a sensitivity penalization based robust state estimator is adopted in this paper for revealing the structure of a grn based on the specific structure of the estimation problem it has been proved that under some weak conditions both the ekf based method and the method suggested in this paper provide a consistent estimate but the suggested method has a faster convergence speed compared with both the ekf and the unscented kalman filter ukf based methods simulation results and real data based estimations consistently show that both convergence speed and parametric estimation accuracy can be appreciably improved these lead to significant reductions in both false positive errors and false negative errors and may imply helpfulness of the suggested method in better understanding the structure and dynamics of actual grns

observer design of discrete time impulsive switched nonlinear systems with time varying delays this paper investigates the problem of observer design for discrete time impulsive switched nonlinear systems with time varying delays firstly based on the average dwell time approach and the lyapunov krasovskii functional technique a delay dependent exponential stability criterion for the discrete time impulsive switched nonlinear systems with time varying delays is derived in terms of a set of linear matrix inequalities lmis then sufficient conditions for the existence of an observer that guarantees the exponential stability of the corresponding error system are proposed finally two numerical examples are given to illustrate the effectiveness of the proposed method

quadratic stabilization of continuous time systems with state delay and norm bounded time varying uncertainties this paper develops a method for designing a feedback control law to stabilize a class of uncertain linear systems the class of systems under consideration is described by a continuous time model with variable state delay and depends on time varying unknown but bounded uncertain parameters it is shown that the construction of the stabilizing controller involves solving a certain algebraic riccati equation several previous results are derived as interesting special cases finally a simulation example is presented to illustrate the analytical developments

fuzzy controller design for nonlinear impulsive fuzzy systems with time delay the stabilization problem is investigated for continuous time takagi sugeno t s fuzzy systems with time delay and impulsive effects in this paper some delay independent and delay dependent stabilization approaches are developed for both state feedback and observer based feedback cases which are based on the lyapunov krasovskii functional approach and a parallel distributed compensation scheme the time delay is dealt by lyapunov theory allied with the halanay lemma the restriction on the interval between each impulsive instant and output sampled instant needs not be equal to or less than a constant scalar but it only requires an inequality satisfaction when the impulsive effects vanish the results can be extended to the corresponding sufficient conditions for the cases of a nonlinear continuous time delay system with a state feedback and observer based sampled output feedback finally some examples are given to demonstrate the effectiveness of the proposed method

synchronization control for nonlinear stochastic dynamical networks pinning impulsive strategy in this paper a new control strategy is proposed for the synchronization of stochastic dynamical networks with nonlinear coupling pinning state feedback controllers have been proved to be effective for synchronization control of state coupled dynamical networks we will show that pinning impulsive controllers are also effective for synchronization control of the above mentioned dynamical networks some generic mean square stability criteria are derived in terms of algebraic conditions which guarantee that the whole state coupled dynamical network can be forced to some desired trajectory by placing impulsive controllers on a small fraction of nodes an effective method is given to select the nodes which should be controlled at each impulsive constants the proportion of the controlled nodes guaranteeing the stability is explicitly obtained and the synchronization region is also derived and clearly plotted numerical simulations are exploited to demonstrate the effectiveness of the pinning impulsive strategy proposed in this paper

stability of uncertain quasi periodic hybrid dynamic systems this paper derives sufficient conditions for the stability of uncertain quasi periodic hybrid dynamic systems these conditions do not require the lyapunov function to be non increasing along each trajectory of the continuous variable dynamic system cvds in other words they do not require every cvds to be stable and they also do not require the lyapunov function to be non increasing along the whole sequence of the switchings furthermore they do not require the knowledge of the continuous trajectory with the proposed conditions the stability bounds for structured perturbations characterized by non negative matrices that still ensure robust stability are derived

impulsive multiconsensus of second order multiagent networks using sampled position data a multiconsensus problem of multiagent networks is solved in this paper where multiconsensus refers to that the states of multiple agents in each subnetwork asymptotically converge to an individual consistent value when there exist information exchanges among subnetworks a distributed impulsive protocol is proposed to achieve multiconsensus of second order multiagent networks in terms of three categories 1 stationary multiconsensus 2 the first dynamic multiconsensus and 3 the second dynamic multiconsensus this impulsive protocol utilizes only sampled position data and is implemented at sampling instants for those three categories of multiconsensus the control parameters in the impulsive protocol are designed respectively moreover necessary and sufficient conditions are derived under which each multiconsensus can be reached asymptotically several simulations are finally provided to demonstrate the effectiveness of the obtained theoretical results

memoryless stabilization of uncertain dynamic delay systems riccati equation approach the authors present a procedure for obtaining the memoryless linear state feedback control of uncertain dynamic delay systems the uncertainties are time varying and within a given compact set this method is an extension of the riccati equation approach proposed by i r petersen and c v hollot 1986 the extension is straightforward also the uncertainties do not need to satisfy the matching conditions

convergence domain for time varying switched systems abstract in this paper we investigate the convergence domain for time varying switched systems we construct multiple lyapunov functions and each lyapunov function is decreasing outside a ball whose radius is time varying we give a relatively accurate convergence domain for a general time varying switched system finally a numerical example a mass spring damper system is provided to show the effectiveness of the theoretical results

finite time dissipative control for stochastic interval systems with time delay and markovian switching the finite time stochastically boundedness ftsb and the finite time strictly stochastically exponential dissipative ftssed control problems for the stochastic interval systems which are encountered the time delay and markovian switching are investigated in this paper the stochastic delayed interval systems with markovian switching sdisswms are equivalently transformed into a kind of stochastic uncertain time delay systems with markovian switching by interval matrix transformation some sufficient conditions of ftsb and ftssed for the stochastic delayed interval systems with markovian switching are obtained and the ftsb and ftssed controllers are designed by solving a series of linear matrix inequalities which are solvable by lmis toolbox finally a numerical example with simulations is given to illustrate the correctness of the obtained results and the effectiveness of the designed controller

reliable dissipative control for stochastic impulsive systems this paper deals with the problem of reliable dissipative control for a class of stochastic hybrid systems the systems under study are subject to markovian jump parameter uncertainties possible actuator failure and impulsive effects which are often encountered in practice and the sources of instability our attention is focused on the design of linear state feedback controllers and impulsive controllers such that for all admissible uncertainties as well as actuator failure occurring among a prespecified subset of actuators the stochastic hybrid system is stochastically robustly stable and strictly q s r dissipative the sufficient conditions are obtained by using linear matrix inequality lmi techniques the main results of this paper extend the existing results on h control

control of markovian jump discrete time systems with norm bounded uncertainty and unknown delay this paper studies the problem of control for discrete time delay linear systems with markovian jump parameters the system under consideration is subjected to both time varying norm bounded parameter uncertainty and unknown time delay in the state and markovian jump parameters in all system matrices we address the problem of robust state feedback control in which both robust stochastic stability and a prescribed h sub spl infin performance are required to be achieved irrespective of the uncertainty and time delay it is shown that the above problem can be solved if a set of coupled linear matrix inequalities has a solution

robust kalman filtering for uncertain systems abstract this paper studies the problem of kalman filter design for uncertain systems the system under consideration is subjected to time varying norm bounded parameter uncertainties in both the state and measurement matrices the problem we address is the design of a state estimator such that the covariance of the estimation error is guaranteed to be within a certain bound for all admissible uncertainties a riccati equation approach is proposed to solve the above problem furthermore a suboptimal covariance upper bound can be computed by a convex optimization

exponential synchronization of linearly coupled neural networks with impulsive disturbances this brief investigates globally exponential synchronization for linearly coupled neural networks nns with time varying delay and impulsive disturbances since the impulsive effects discussed in this brief are regarded as disturbances the impulses should not happen too frequently the concept of average impulsive interval is used to formalize this phenomenon by referring to an impulsive delay differential inequality we investigate the globally exponential synchronization of linearly coupled nns with impulsive disturbances the derived sufficient condition is closely related with the time delay impulse strengths average impulsive interval and coupling structure of the systems the obtained criterion is given in terms of an algebraic inequality which is easy to be verified and hence our result is valid for large scale systems the results extend and improve upon earlier work as a numerical example a small world network composing of impulsive coupled chaotic delayed nn nodes is given to illustrate our theoretical result

stability and l2 gain analysis for switched delay systems a delay dependent method in this paper we study stability and l 2 gain for a class of switched systems with time varying delays sufficient conditions for exponential stability and weighted l 2 gain are developed for a class of switching signals with average dwell time these conditions are delay dependent and are given in the form of linear matrix inequalities lmis as a special case of such switching signals we can obtain exponential stability and normal l 2 gain under arbitrary switching signals the state decay estimate is explicitly given two examples illustrate the effectiveness and applicability of the proposed method

on hybrid impulsive and switching systems and application to nonlinear control in this note a new class of hybrid impulsive and switching models is introduced and their asymptotic stability properties are investigated using switched lyapunov functions some new general criteria for exponential stability and asymptotic stability with arbitrary and conditioned impulsive switching are established in addition a new hybrid impulsive and switching control strategy for nonlinear systems is developed a typical example the unified chaotic system is given to illustrate the theoretical results

biometrika centenary sample surveys summary despite karl pearson s stated aim that the evolutionist has to become in the widest sense of the words a registrar general for all forms of life the papers published in biometrika on sample surveys have been mainly theoretical and do not start to appear until the 1940s there has been little work on sampling in the life sciences with the exception of capture recapture methods the major areas have been in variable probability designs the foundations of inference for finite populations analytic surveys and the role of selection mechanisms in inference in recent years the work on survey analysis has been the outcome of an interaction between sample selection mechanisms and mainstream theory with interesting consequences for both areas

intrinsically bayesian robust kalman filter an innovation process approach in many contemporary engineering problems model uncertainty is inherent because accurate system identification is virtually impossible owing to system complexity or lack of data on account of availability time or cost the situation can be treated by assuming that the true model belongs to an uncertainty class of models in this context an intrinsically bayesian robust ibr filter is one that is optimal relative to the cost function in the classical sense and the prior distribution over the uncertainty class in the bayesian sense ibr filters have previously been found for both wiener and granulometric morphological filtering in this paper we derive the ibr kalman filter that performs optimally relative to an uncertainty class of state space models introducing the notion of bayesian innovation process and the bayesian orthogonality principle we show how the problem of designing an ibr kalman filter can be reduced to a recursive system similar to the classical kalman recursive equations except with effective counterparts such as the effective kalman gain matrix after deriving the recursive ibr kalman equations for discrete time we use the limiting method to obtain the ibr kalman bucy equations for continuous time finally we demonstrate the utility of the proposed framework for two real world problems sensor networks and gene regulatory network inference

non linear impulsive dynamical systems part i stability and dissipativity in this paper we develop lyapunov and invariant set stability theorems for non linear impulsive dynamical systems furthermore we generalize dissipativity theory to non linear dynamical systems with impulsive effects specifically the classical concepts of system storage functions and supply rates are extended to impulsive dynamical systems providing a generalized hybrid system energy interpretation in terms of stored energy dissipated energy over the continuous time system dynamics and dissipated energy over the resetting instants furthermore extended kalman yakubovich popov conditions in terms of the impulsive system dynamics characterizing dissipativeness via system storage functions are derived finally the framework is specialized to passive and non expansive impulsive systems to provide a generalization of the classical notions of passivity and non expansivity for non linear impulsive systems these results are used in the second part of this paper to develop extensions of the small gain and p

jump linear quadratic control with random state discontinuities abstract in a random environment jump linear quadratic control problems are studied random state discontinuities are included in the analysis and the corresponding optimal regulator is obtained the introduction of stochastic notions of stabilizability and detectability gives a direct characterization of the asymptotic behaviour of the optimal system

reliable control design of fuzzy dynamic systems with time varying delay this paper focuses on the reliable fuzzy control design problem for fuzzy control systems with time delay based on linear matrix inequality lmi approach a method for designing a reliable fuzzy controller is presented the resulting fuzzy control systems are reliable in the sense that asymptotic stability is achieved not only when all control components are operating well but also in the presence of some component failures a reliable fuzzy control design scheme via state feedback is proposed in terms of lmis the result is extended to the case of observer based reliable fuzzy control two illustrative examples are given to illustrate the validity of the proposed design procedures

impulsive consensus algorithms for second order multi agent networks with sampled information in this paper the distributed consensus problem for second order continuous time multi agent networks with sampled data communication is investigated motivated by impulsive control strategy two kinds of impulsive distributed consensus algorithm are proposed these algorithms only utilize the sampled information and are implemented at sampled times by using the stability theory of impulsive systems and properties of the laplacian matrix necessary and sufficient conditions are obtained to ensure the consensus of the controlled networks it is shown that the control gains the sampling period and the eigenvalues of the laplacian matrix of the communication graph play key roles in achieving the consensus a numerical example is given to illustrate the results

brief paper a unified synchronization criterion for impulsive dynamical networks this paper focuses on the problem of globally exponential synchronization of impulsive dynamical networks two types of impulses are considered synchronizing impulses and desynchronizing impulses in previous literature all of the results are devoted to investigating these two kinds of impulses separately thus a natural question arises is there any unified synchronization criterion which is simultaneously effective for synchronizing impulses and desynchronizing impulses in this paper a unified synchronization criterion is derived for directed impulsive dynamical networks by proposing a concept named average impulsive interval the derived criterion is theoretically and numerically proved to be less conservative than existing results numerical examples including scale free and small world structures are given to show that our results are applicable to large scale networks

robust h control for stochastic systems with nonlinearity uncertainty and time varying delay this paper deals with the problems of robust stochastic stabilization and h control for uncertain stochastic systems with time varying delay and nonlinear perturbation system uncertainties are assumed to be norm bounded and time delay is assumed to be bound and time varying with delay derivative bounded by a constant which may be greater than one first new delay dependent criterion is proposed by exploiting delay partitioned lyapunov krasovskii functional and by employing tighter integral equalities to estimate the upper bound of the stochastic differential of lyapunov krasovskii functional without ignoring some useful terms second based on the criterion obtained a delay dependent criterion for the existence of a state feedback h controller that ensures robust stochastic stability and a prescribed h performance level of the closed loop system for all admissible uncertainties is proposed these developed results have advantages over some previous ones in that they involve fewer matrix variables but have less conservatism and they also enlarge the application scope new sufficient conditions are presented in terms of linear matrix inequality numerical examples are used to illustrate the effectiveness and feasibility of the proposed method

a tutorial on particle filters for online nonlinear non gaussian bayesian tracking increasingly for many application areas it is becoming important to include elements of nonlinearity and non gaussianity in order to model accurately the underlying dynamics of a physical system moreover it is typically crucial to process data on line as it arrives both from the point of view of storage costs as well as for rapid adaptation to changing signal characteristics in this paper we review both optimal and suboptimal bayesian algorithms for nonlinear non gaussian tracking problems with a focus on particle filters particle filters are sequential monte carlo methods based on point mass or particle representations of probability densities which can be applied to any state space model and which generalize the traditional kalman filtering methods several variants of the particle filter such as sir asir and rpf are introduced within a generic framework of the sequential importance sampling sis algorithm these are discussed and compared with the standard ekf through an illustrative example

stochastic stability of the discrete time extended kalman filter the authors analyze the error behavior for the discrete time extended kalman filter for general nonlinear systems in a stochastic framework in particular it is shown that the estimation error remains bounded if the system satisfies the nonlinear observability rank condition and the initial estimation error as well as the disturbing noise terms are small enough this result is verified by numerical simulations for an example system

filtering of two dimensional periodic roesser systems subject to dissipativity abstract in this note the problem of dissipativity based filtering of two dimensional 2d periodic roesser systems is investigated a discrete time periodic roesser model extensively used in practical systems is introduced to describe 2d periodic systems moreover it is assumed that the periods of the augmented system in horizontal and vertical directions are the same which can greatly simplify stability analyses by resorting to the periodic lyapunov functional approach that depends on periodical property of the augmented system less conservative results for the existence of 2d periodic filter are presented to ensure the asymptotic stability and 2d q 1 q 2 q 3 dissipativity particularly the parameters of 2d periodic filter are derived with convex optimization method simulation results are provided to verify the effectiveness and merits of the theoretical findings in addition the correlation between optimal dissipative performance indices and different lyapunov functions is revealed

delay dependent robust stability and h control for jump linear systems with delays abstract this paper considers robust stochastic stability stabilization and h control problems for a class of jump linear systems with time delays by using some zero equations neither model transformation nor bounding for cross terms is required to obtain the delay dependent results which are given in terms of linear matrix inequalities lmis maximum sizes of time delays are also studied for system stability furthermore solvability conditions and corresponding h control laws are given which provide robust stabilization with a prescribed h disturbance attenuation level numerical examples show that the proposed methods are much less conservative than existing results

hybrid stabilization and synchronization of nonlinear systems with unbounded delays the stabilization of nonlinear systems with bounded and unbounded time delays via hybrid control is studied we investigate and identify switching rules for which stabilization can be verified a priori when this approach is inadequate stabilizing state dependent switching rules are constructed this method is based on partitioning the state space into switching regions unwanted physical behavior such as chattering and zeno behavior is avoided sufficient conditions are established using razumikhin like theorems the theoretical results provide insight into how hybrid control strategies can be constructed to synchronize a class of nonlinear systems with unbounded delay the findings are illustrated through numerical simulations

technical communique robust reliable control for a class of uncertain nonlinear state delayed systems this paper deals with the problem of robust reliable control design for a class of nonlinear uncertain state delayed systems the system under consideration involves state time delay parameter uncertainties and unknown nonlinear disturbances the nonlinearities are assumed to satisfy the boundedness condition and the parameter uncertainties are allowed to be time varying unstructured the purpose of this problem is to design the state feedback controller such that for all admissible uncertainties as well as actuator failures occuring among a prespecified subset of actuators the plant remains globally exponentially stable independently of the time delay an effective modified algebraic riccati equation approach is developed to solve the problem addressed it is shown that designed nonlinear time delay control systems provide guaranteed robust reliable stability despite possible actuator failures we present an illustrative example to demonstrate the applicability of the proposed design approach

robust stabilization of uncertain linear systems quadratic stabilizability and h sup infinity control theory the problem of robustly stabilizing a linear uncertain system is considered with emphasis on the interplay between the time domain results on the quadratic stabilization of uncertain systems and the frequency domain results on h sup infinity optimization a complete solution to a certain quadratic stabilization problem in which uncertainty enters both the state and the input matrices of the system is given relations between these robust stabilization problems and h sup infinity control theory are explored it is also shown that in a number of cases if a robust stabilization problem can be solved via lyapunov methods then it can be also be solved via h sup infinity control theory based methods

on optimal control problems of a class of impulsive switching systems with terminal states constraints abstract the global optimal control problem is proposed for a special class of hybrid dynamical systems i e impulsive switching systems then the necessary condition of the above problem the minimum principle is given ekeland s variational principle and the matrix cost functional structure expression are utilized in the process of the proof based on the main result a special linear hybrid impulsive and switching system hiss is illustrated and the optimal control algorithm is presented moreover the cases of pure impulsive systems and pure switched systems are included in this paper

reliable h sub spl infin control for affine nonlinear systems this paper addresses the reliable h sub spl infin control problems for affine nonlinear systems based on the hamilton jacobi inequality approach developed in the h spl infin control problems for affine nonlinear systems a method for the design of reliable nonlinear control systems is presented the resulting nonlinear control systems are reliable in that they provide guaranteed local asymptotic stability and h sub spl infin performance not only when all control components are operational but also in the case of some component outages within a prespecified subset of control components a numerical example is also given

impulse differential inclusions a viability approach to hybrid systems impulse differential inclusions are introduced as a framework for modeling hybrid phenomena connections to standard problems in the area of hybrid systems are discussed conditions are derived that allow one to determine whether a set of states is viable or invariant under the action of an impulse differential inclusion for sets that violate these conditions methods are developed for approximating their viability and invariance kernels that is the largest subset that is viable or invariant under the action of the impulse differential inclusion the results are demonstrated on examples

analysis of novel stochastic switched sili epidemic models with continuous and impulsive control abstract in this paper we establish two new stochastic switched epidemic models with continuous and impulsive control the stochastic perturbations are considered for the natural death rate in each equation of the models firstly a stochastic switched s i l i model with continuous control schemes is investigated by using lyapunov razumikhin method the sufficient conditions for extinction in mean are established our result shows that the disease could be die out theoretically if threshold value r is less than one regardless of whether the disease free solutions of the corresponding subsystems are stable or unstable then a stochastic switched s i l i model with continuous control schemes and pulse vaccination is studied the threshold value r is derived the global attractivity of the model is also obtained at last numerical simulations are carried out to support our results

robust stability of quasi periodic hybrid dynamic uncertain systems considers the robust stability of quasi periodic hybrid dynamic systems hdss with polytopic uncertainties the quasi periodic hdss has infinite switchings but the switching sequence forms a cycle and the cycle is repeated we derive the stability conditions for quasi periodic hds with uncertainties in continuous variable dynamic systems and with variations in both the switching conditional set and the reset map by analyzing the behavior of the system along the cycle the results require the lyapunov function to be bounded by a continuous function along each continuous variable dynamic system and is nonincreasing along a subsequence of the switchings they do not require the lyapunov function to be nonincreasing along the whole sequence of the switchings

open loop nash equilibrium in polynomial differential games via state dependent riccati equation this paper studies finite as well as infinite time horizon nonzero sum polynomial differential games in both cases we explore the so called state dependent riccati equations to find a set of strategies that guarantee an open loop nash equilibrium for this particular class of nonlinear games such a method presents advantages in simplicity of the design of equilibrium strategies and yields computationally effective solution algorithms we demonstrate that this solution leads the game to an e or quasi equilibrium and provide an upper bound for this e quantity the proposed solution is given as a set of n coupled polynomial riccati like state dependent differential equations where each equation includes a p linear form tensor representation for its polynomial part we provide an algorithm for finding the solution of the state dependent algebraic equation in the infinite time case based on a hamiltonian approach and give conditions on the existence of such stabilizing solutions for a third order polynomial a numerical example is presented to illustrate effectiveness of the approach

consensus of second order multi agent systems via impulsive control using sampled hetero information in this paper the consensus problem for second order multi agent systems using impulsive control with sampled hetero information is investigated necessary and sufficient conditions for sampling interval to achieve consensus for the second order multi agent systems are obtained analysis for the upper bound of sampling interval convergence performance and communication cost of the proposed control protocols are also discussed some numerical examples are given to demonstrate the effectiveness of the proposed control protocols

robust h state feedback control for linear systems with state delay and parameter uncertainty this paper addresses the problem of robust h state feedback control design for linear systems with state delay and parameter uncertainty based on a positive definite solution of a modified algebraic riccati equation the proposed robust h static state feedback controller stabilizes uncertain time delay systems independently of delays and guarantees an h norm bound constraint on disturbance attenuation for all admissible uncertainties furthermore it is shown that no advantage can be obtained from the use of a proper linear dynamic state feedback compared with the use of static state feedback illustrative examples are given to demonstrate the applicability of the proposed approach

a kernel method for estimating finite population distribution functions using auxiliary information summary this paper considers the use of auxiliary information to improve the estimation of the distribution function of a finite population a method is proposed which combines the known distribution of the auxiliary variable with a kernel estimate of the conditional distribution of the survey variable given the value of the auxiliary variable the resulting estimator compares favourably with existing estimators in terms of efficiency conditional behaviour and robustness the proposed method also has the advantage of producing estimates which are bona fide distribution functions this is not the case for many calibration type estimators suggested in the literature finally the proposed method is applicable under any probability sampling scheme