brief robust h filtering for uncertain impulsive stochastic systems under sampled measurements this paper is concerned with the problem of robust h filtering for uncertain impulsive stochastic systems under sampled measurements the parameter uncertainties are assumed to be time varying norm bounded the aim is to design a stochastically stable filter using the locally sampled measurements which ensures both the robust stochastic stability and a prescribed level of h performance for the filtering error dynamics for all admissible uncertainties a sufficient condition for the existence of such a filter is proposed in terms of certain linear matrix inequalities lmis when these lmis are feasible an explicit expression of a desired filter is given an example is provided to demonstrate the effectiveness of the proposed approach

approximate finite dimensional filtering for polynomial states over polynomial observations in this article the mean square filtering problem for polynomial system states over polynomial observations is studied proceeding from the general expression for the stochastic ito differentials o

attractors for the semilinear reaction diffusion equation with distribution derivatives in unbounded domains abstract in this paper we prove the existence of global attractors for a nonlinear reaction diffusion equation with a nonlinearity having a polynomial growth of arbitrary order p 1 p 2 and with distribution derivatives in the inhomogeneous term the global attractors are obtained in l 2 r n and l p r n respectively a new a priori estimate method has been used since the solutions of the equation have no higher regularity and the semigroup associated with the solutions is not continuous in l p r n the results are new and appear to be optimal

solution of the h sub infinity optimal linear filtering problem for discrete time systems the solution of l sub 2 minimum variance and h sub infinity estimation problems is considered using a polynomial systems approach the results for the l sub 2 filtering problem which corresponds with wiener or kalman filtering prediction are first presented in polynomial matrix form attention then turns to the solution of the h sub infinity estimation problem for scalar systems numerous examples are presented to illustrate the computational procedures the two types of estimator are appropriate to very different estimation problems and the new h sub infinity devices should be valuable in certain application areas

h control for discrete time linear systems with frobenius norm bounded uncertainties in this paper we consider the problems of robust stability and control for the class of uncertain discrete time linear systems with frobenius norm bounded parameter uncertainties in all matrices of the system and output equations necessary and sufficient conditions for the above problems are proposed a linear static state feedback control law is designed which is in terms of a riccati inequality the results obtained here show that the robust control problem of the uncertain system is equivalent to the control problem for a corresponding uncertainty free system

reduced order generalized h_ infty filtering for linear discrete time systems with application to channel equalization this paper investigates the problem of reduced order generalized h infty filtering for linear discrete time systems generalized h infty filtering covers standard h infty filtering as a special case and can make use of the frequency domain characteristics of practical signals moreover reduced order filters are more attractive than full order ones regarding implementability by virtue of the generalized bounded real lemma a new necessary and sufficient condition is proposed for analyzing the generalized h infty performance of the filtering error system to compute reduced order generalized h infty filters a necessary and sufficient condition is then derived in terms of matrix inequalities to solve which iterative linear matrix inequality algorithms are further developed in addition the proposed filter design method is applied to cope with the channel equalization problem examples are finally presented for illustrating the proposed method

stochastic stability and robust control for sampled data systems with markovian jump parameters in this paper the problems of stochastic stability and robust control for a class of uncertain sampled data systems are studied the systems consist of random jumping parameters described by finite state semi markov process sufficient conditions for stochastic stability or exponential mean square stability of the systems are presented the conditions for the existence of a sampled data feedback control and a multirate sampled data optimal control for the continuous time uncertain markovian jump systems are also obtained the design procedure for robust multirate sampled data control is formulated as linear matrix inequalities lmis which can be solved efficiently by available software toolboxes finally a numerical example is given to demonstrate the feasibility and effectiveness of the proposed techniques

upper semicontinuity of the attractor for a singularly perturbed hyperbolic equation abstract for a smooth bounded domain r n n 3 and e a real parameter consider the hyperbolic equation eu tt u t u u g in with dirichlet boundary conditions under certain conditions on this equation has a compact attractor a e in h 0 1 l 2 for e 0 the parabolic equation also has a compact attractor which can be naturally embedded into a compact set a 0 in h 0 1 l 2 it is shown that for any neighborhood u of a 0 the set a e u for e small

adaptive fuzzy control for uncertain interconnected time delay systems in this paper the problem of control for a class of uncertain interconnected time delay systems is studied the interconnections of the system possess time varying delay characteristics and the bounds of uncertainties are not precisely known a decentralized adaptive feedback controller is designed which is independent of the delays lyapunov krasovskii approach is employed to show that the corresponding closed loop system is asymptotically stable a simulation example is given to demonstrate the potential of the proposed techniques

filtering on sampled data systems with parametric uncertainty the paper is concerned with the problem of robust h sub spl infin filtering for a class of systems with parametric uncertainties and unknown time delays under sampled measurements the parameter uncertainties considered are real time varying and norm bounded appearing in the state equation an approach has been proposed for the designing of h sub spl infin filters using sampled measurements which would guarantee a prescribed h sub spl infin performance in the continuous time context irrespective of the parameter uncertainties and unknown time delays both cases of finite and infinite horizon filtering are studied it has been shown that the above robust h sub spl infin filtering problem can be solved in terms of differential riccati inequalities with finite discrete jumps

on designing filters for uncertain sampled data nonlinear systems abstract this paper is concerned with the problem of nonlinear h filtering for sampled data systems with nonlinear time varying parameter uncertainty the aim is to design a digital filter such that the ratio between the energy of the estimation errors and the energy of the exogenous inputs is minimised or guaranteed to be less or equal to a prescribed value for all admissible uncertainties a nonlinear bounded real lemma for sampled data systems with nonlinear time varying parameter uncertainty is provided based on this nonlinear bounded real lemma the robust h filtering problem is solved in terms of both continuous and discrete hamilton jacobi equations

robust h control for linear markovian jump systems with unknown nonlinearities this paper studies the problem of stochastic stability and disturbance attenuation for a class of linear continuous time uncertain systems with markovian jumping parameters the uncertainties are assumed to be nonlinear and state control and external disturbance dependent a sufficient condition is provided to solve the above problem an h controller is designed such that the resulting closed loop system is stochastically stable and has a disturbance attenuation for all admissible uncertainties it is shown that the control law is in terms of the solutions of a set of coupled riccati inequalities a numerical example is included to demonstrate the potential of the proposed technique

the attractor for a nonlinear reaction diffusion system in an unbounded domain in this paper the quasi linear second order parabolic systems of reaction diffusion type in an unbounded domain are considered our aim is to study the long time behavior of parabolic systems for which the nonlinearity depends explicitly on the gradient of the unknown functions to this end we give a systematic study of given parabolic systems and their attractors in weighted sobolev spaces dependence of the hausdorff dimension of attractors on the weight of the sobolev spaces is considered 2001 john wiley sons inc

h _ infty filtering for discrete time state delayed systems with finite frequency specifications this article researches the problem of finite frequency ff h filtering for linear discrete time state delayed systems the disturbance is assumed to reside in low middle high frequency ranges to reduce the conservatism of the results delay partitioning idea is used to derive a new ff bounded real lemma brl by applying the generalized kalman yakubovich popov lemma two equivalent approaches to the proof of the proposed ff brl are given respectively starting from transfer function and lyapunov krasovskii functional a new ff h filter design method is proposed in terms of solving a set of linear matrix inequalities finally a numerical example clearly demonstrates the merits and effectiveness of the proposed method

random attractors for the stochastic benjamin bona mahony equation on unbounded domains abstract we prove the existence of a compact random attractor for the stochastic benjamin bona mahony equation defined on an unbounded domain this random attractor is invariant and attracts every pulled back tempered random set under the forward flow the asymptotic compactness of the random dynamical system is established by a tail estimates method which shows that the solutions are uniformly asymptotically small when space and time variables approach infinity

asymptotic analysis and upper semicontinuity with respect to rotational inertia of attractors to von karman plates with geometrically localized dissipation and critical nonlinearity abstract in this study we consider the von karman evolution equations accounting for rotational inertial forces along with a nonlinear localized damping under suitable hypotheses we prove the existence regularity and finite dimensionality of a compact attractor a r the main result of the paper is upper semicontinuity of attractors with respect to rotational inertia terms the main obstacles are criticality of the nonlinear term of the equation combined with geometrically constrained dissipation the flux multiplier used for propagation of the damping does not cooperate with the nonlinear term which is of critical exponent a new method based on uniform compactness is developed in order to handle such cases the method allows to establish uniform smoothness of the elements from the attractor which is the key ingredient in proving that the attractor is upper semicontinuous with respect to the rotational inertia 0 and conclude that it converges to the attractor a r obtained in the case 0 in geredeli et al 2013 23 when 0

mean square data based controller for nonlinear polynomial systems with multiplicative noise this paper presents the mean square optimal data based quadratic gaussian controller for stochastic nonlinear polynomial systems with a polynomial multiplicative noise a linear control input and a quadratic criterion over linear observations the mean square optimal closed form controller equations are obtained using the separation principle whose applicability to the considered problem is substantiated as an intermediate result the paper gives a closed form solution of the optimal regulator control problem for stochastic nonlinear polynomial systems with a polynomial multiplicative noise a linear control input and a quadratic criterion performance of the obtained mean square optimal data based controller is verified in the illustrative example against the conventional lqg controller that is optimal for linearized systems simulation graphs demonstrating overall performance and computational accuracy of the designed optimal controller are included

h output feedback control of fuzzy system models under sampled measurements this paper studies the problem of control for a class of fuzzy system models by using a linear output controller the system under consideration is described by a continuous time fuzzy system model under sampled output measurements the premise variables of the fuzzy system model are assumed unmeasurable we develop a technique for designing an output feedback control law which globally stabilises this class of fuzzy system models a design algorithm for constructing the linear output controller is given a numerical simulation example is given to show the potential of the proposed techniques

brief paper fault tolerant control for a class of nonlinear sampled data systems via a euler approximate observer in this paper a fault tolerant control ftc scheme is developed for a class of nonlinear sampled data systems first a euler approximate discrete model is used to describe the plant under the sampling under this model an observer based fault estimation method is proposed to guarantee the accuracy of both the state and fault estimation values the conditions to make the approximate model consistent with the exact model are presented then an active fault tolerant controller which has a constraint condition for the sampling time is designed to make the faulty system stable finally an inverted pendulum is used to show the efficiency of the proposed method

optimum h designs under sampled state measurements abstract we present the complete solution to the h optimal control problem when only sampled values of the state are available for linear time varying systems the optimum controller is characterized in terms of the solution of a particular generalized riccati differential equation with the optimum performance determined by the conjugate point conditions associated with a family of generalized riccati differential equations for the infinite horizon time invariant problem however the optimum controller is characterized in terms of the solution of a particular generalized algebraic riccati equation and the performance is determined in terms of the conjugate point conditions of a single generalized riccati equation defined on the longest sampling interval if the distribution of the sampling times is also taken as part of the general design uniform sampling turns out to be optimal for the infinite horizon case while for the finite horizon problem a nonuniform sampling generally leads to a better performance

fault detection for fuzzy systems with intermittent measurements this paper investigates the problem of fault detection for takagi sugeno t s fuzzy systems with intermittent measurements the communication links between the plant and the fault detection filter are assumed to be imperfect i e data packet dropouts occur intermittently which appear typically in a network environment and a stochastic variable satisfying the bernoulli random binary distribution is utilized to model the unreliable communication links the aim is to design a fuzzy fault detection filter such that for all data missing conditions the residual system is stochastically stable and preserves a guaranteed performance the problem is solved through a basis dependent lyapunov function method which is less conservative than the quadratic approach the results are also extended to t s fuzzy systems with time varying parameter uncertainties all the results are formulated in the form of linear matrix inequalities which can be readily solved via standard numerical software two examples are provided to illustrate the usefulness and applicability of the developed theoretical results

robust observers for neutral jumping systems with uncertain information in this paper the problem of designing observer for a class of uncertain neutral systems the uncertainties are parametric and norm bounded both robust observation and robust h observation methods are developed by using linear state delayed observers in case of robust observation sufficient conditions are established for asymptotic stability of the system which is independent of time delay the results are then extended to robust h observation which renders the augmented system asymptotically stable independent of delay with a guaranteed performance measure furthermore a memoryless state estimate feedback is designed to stabilize the closed loop neutral system in all cases the gain matrices are determined by linear matrix inequality approach two numerical examples are presented to illustrate the validity of the theoretical results

asymptotic smoothing and attractors for the generalized benjamin bona mahony equation on r 3 abstract we study the asymptotic behavior of the solutions of the benjamin bona mahony equation defined on r 3 we first provide a sufficient condition to verify the asymptotic compactness of an evolution equation defined in an unbounded domain which involves the littlewood paley projection operators we then prove the existence of an attractor for the benjamin bona mahony equation in the phase space h 1 r 3 by showing the solutions are point dissipative and asymptotic compact finally we establish the regularity of the attractor and show that the attractor is bounded in h 2 r 3

new results on h filtering for fuzzy systems with interval time varying delays this paper investigates the problem of h filtering for continuous takagi sugeno t s fuzzy systems with an interval time varying delay in the state based on the delay partitioning idea a new approach is proposed for solving this problem which can achieve much less conservative feasibility conditions the attention is focused on the design of an h filter via the parallel distributed compensation scheme such that the filter error system is asymptotically stable and the h attenuation level from disturbance to estimation error is below a prescribed scalar the constructed lyapunov krasovskii functional by applying the delay partitioning method can potentially guarantee the obtained delay dependent conditions to be less conservative than those in the literature the obtained results are formulated in the form of linear matrix inequalities lmis which can be readily solved via standard numerical software finally an example is illustrated to show the reduction in conservatism of the proposed filter design method

steady state kalman filtering with an h error bound abstract an estimator design problem is considered which involves both l 2 least squares and h worst case frequency domain aspects specifically the goal of the problem is to minimize an l 2 state estimation error criterion subject to a prespecified h constraint on the state estimation error the h estimation error constraint is embedded within the optimization process by replacing the covariance lyapunov equation by a riccati equation whose solution leads to an upper bound on the l 2 state estimation error the principal result is a sufficient condition for characterizing fixed order i e full and reduced order estimators with bounded l 2 and h estimation error the sufficient condition involves a system of modified riccati equations coupled by an oblique projection i e idempotent matrix when the h constraint is absent the sufficient condition specializes to the l 2 state estimation result given in 2

sampled data synchronization of chaotic lur e systems with time delays this paper studies the problem of sampled data control for master slave synchronization schemes that consist of identical chaotic lur e systems with time delays it is assumed that the sampling periods are arbitrarily varying but bounded in order to take full advantage of the available information about the actual sampling pattern a novel lyapunov functional is proposed which is positive definite at sampling times but not necessarily positive definite inside the sampling intervals based on the lyapunov functional an exponential synchronization criterion is derived by analyzing the corresponding synchronization error systems the desired sampled data controller is designed by a linear matrix inequality approach the effectiveness and reduced conservatism of the developed results are demonstrated by the numerical simulations of chua s circuit and neural network

attractors for reaction diffusion equations in unbounded domains abstract in this paper we study the asymptotic behaviour of solutions for parabolic non linear evolution equations in r n we prove the asymptotic compactness of the solutions and then establish the existence of the global attractor in l 2 r n

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

two dimensional peak to peak filtering for stochastic fornasini marchesini systems this paper is concerned with the problem of two dimensional 2 d stochastic peak to peak filter design for fornasini marchesini local state space fm lss systems with state multiplicative noise first a novel sufficient condition is established which guarantees that the underlying fm lss system is stochastically mean square stable with 2 d stochastic peak to peak performance a deterministic fm lss system case is also discussed subsequently based on the result a new 2 d stochastic peak to peak filter of general form is designed for fm lss systems with state multiplicative noise finally a numerical example is presented to show the effectiveness of the proposed 2 d stochastic peak to peak filter

h and h 2 filtering for linear systems with uncertain markov transitions this paper is concerned with h and h 2 filtering for markovian jump linear systems with uncertain transition probabilities motivated by the fact that the existing results either impose severe restrictions on some key matrices or introduce some unnecessary matrix variables this paper is focused on developing a new approach to systematically relax these restrictions for filter design by applying a novel technique to eliminate the product terms between the lyapunov matrices and the filter parameters an improved condition is first obtained for analyzing the h performance of the filtering error system then sufficient conditions in terms of linear matrix inequalities are presented for designing filters with a guaranteed h filtering performance level the proposed method is further extended to h 2 filtering theoretical analyses followed by a few numerical examples show that the proposed filter design method outperforms some existing results with respect to reduction of conservatism or variables needed for computation the filter design problems for both continuous time and discrete time markovian jump linear systems are addressed in a unified framework

h filter design for discrete delay systems a new parameter dependent approach this article revisits the problem of h filtering for discrete time systems with a time varying delay in the state and parameter uncertainties residing in a polytope by utilising the polynomially parameter dependent idea a new filter design procedure is proposed which formulates the existence of admissible robust h filters into a set of linear matrix inequalities these conditions are developed based on homogeneous polynomially parameter dependent matrices of an arbitrary degree as the degree grows test of increasing precision is obtained providing less conservative filter designs it is established that the results in the quadratic framework that entail fixed matrices for the entire uncertainty domain and the linearly parameter dependent framework that use linear convex combinations of matrices are special cases of the proposed conditions for the zeroth degree and the first degree respectively moreover in addition to parameter dependence the obtained conditions are also dependent on both

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

stabilization of sampled data control systems with control inputs missing this note is concerned with the stabilization problem for sampled data control systems with control inputs missing a sufficient condition is derived for the existence of exponentially stabilizing state feedback controllers via the switched system approach the obtained condition establishes several quantitative relations among some system parameters such as the sampling period and the exponential decay rate the actual data missing rate and the admissible data missing rate bound two illustrative examples are given to show the effectiveness of the proposed results

robust kalman filtering for discrete time markovian jump systems with parameter uncertainty in this paper we examine the problem of robust kalman filtering for a class of linear uncertain discrete time systems with markovian jump parameters the underlying system is subjected to norm bounded time varying uncertainties in the state and measurement equations first stochastic quadratic stability of the system is studied then a linear state estimator is constructed such that the estimation error covariance is guaranteed to lie within certain bound for all admissible uncertainties the solution is given in terms of two coupled algebraic riccati equations

global attractors for the klein gordon schrodinger equation in unbounded domains abstract in this paper we study the long time behavior of solutions for the klein gordon schrodinger equation in the whole space r n with n 3 we first prove the continuity of the solutions on initial data and then establish the asymptotic compactness of solutions finally we show the existence of the global attractor for this model in the space hk r n hk r n for each integer k 1

on the dynamics of a class of nonclassical parabolic equations abstract we consider the first initial and boundary value problem of nonclassical parabolic equations u t u t u g u f x on a bounded domain where 0 1 first we establish some uniform decay estimates for the solutions of the problem which are independent of the parameter then we prove the continuity of solutions as 0 finally we show that the problem has a unique global attractor a in v 2 h 2 h 0 1 in the topology of h 2 moreover a a 0 in the sense of hausdorff semidistance in h 0 1 as goes to 0

sampled data fuzzy control of chaotic systems based on a t s fuzzy model in this paper a sampled data fuzzy controller is designed to stabilize a class of chaotic systems a takagi sugeno t s fuzzy model is employed to represent the chaotic systems based on this general model the exponential stability issue of the closed loop systems with an input constraint is first investigated by a novel time dependent lyapunov functional which is positive definite at sampling times but not necessary between the sampling times then two sufficient conditions are developed for sampled data fuzzy controller synthesis of the underlying t s fuzzy model with or without input constraint all the proposed results in this paper depend on both the upper and lower bounds on a sampling interval and the available information about the actual sampling pattern is fully utilized the proposed sampled data fuzzy control scheme is successfully applied to the chaotic lorenz system which is shown to be effective and less conservative compared with existing results

upper semicontinuity of pullback attractors for nonclassical diffusion equations our aim in this paper is to study the long time behavior in terms of upper semicontinuous property of pullback attractors of nonclassical diffusion equations with nonautonomous perturbation specifically we prove that under some proper assumptions the pullback attractor ae t t r of eq 1 and the global attractor a of eq 1 with e 0 satisfy lime 0 distx ae t a 0 for any t r

upper semicontinuity of attractors for nonclassical diffusion equations in h1 r3 abstract in this paper we mainly investigate upper semicontinuity of global attractors in h 1 r 3 for a perturbed nonclassical diffusion equations for this purpose some necessary abstract results are established

h_ bm infty fuzzy filtering of nonlinear systems with intermittent measurements this paper is concerned with the problem of h infin fuzzy filtering of nonlinear systems with intermittent measurements the nonlinear plant is represented by a takagi sugeno t s fuzzy model the measurements transmission from the plant to the filter is assumed to be imperfect and a stochastic variable satisfying the bernoulli random binary distribution is utilized to model the phenomenon of the missing measurements attention is focused on the design of an h infin filter such that the filter error system is stochastically stable and preserves a guaranteed h infin performance a basis dependent lyapunov function approach is developed to design the h infin filter by introducing some slack matrix variables the coupling between the lyapunov matrix and the system matrices is eliminated which greatly facilitates the filter design procedure the developed theoretical results are in the form of linear matrix inequalities lmis finally an illustrative example is provided to show the effectiveness of the proposed approach

h filtering for linear periodic systems with parameter uncertainty abstract this paper focuses on h filtering for a class of linear periodic systems with a certain type of norm bounded time varying parameter uncertainty which appears in both the state and output matrices the problem addressed is the design of a linear periodic estimator that guarantees both the quadratic stability and and prescribed h performance on infinite horizon for the estimation error for all admissible parameter uncertainties a solution to this problem is obtained via a riccati equation approach

finite frequency h_ infty deconvolution with application to approximated bandlimited signal recovery this paper investigates a finite frequency h infty deconvolution problem for single input single output discrete time systems motivated by the fact that many practical signals are located in a finite frequency range this paper is focused on developing a design method for achieving better deconvolution performance over a finite frequency range first a finite frequency h infty deconvolution problem is formulated such that the deconvolution specification is characterized by a modified h mathbf infty index associated with the corresponding finite frequency range by an adapted generalized kalman yakubovich popov lemma and an auxiliary vector approach a matrix inequality condition is obtained for parameterizing a required deconvolution filter based on which a simple iterative algorithm is then constructed for optimizing the filter performance multiobjective deconvolution is further discussed in the same framework compared with the traditional frequency weighting strategy the proposed method can directly analyze and synthesize the deconvolution performance within finite frequency ranges the advantage of which is demonstrated in a bandlimited signal recovery example

optimal guaranteed cost control of uncertain discrete time delay systems this paper considers the problem of robust guaranteed cost control of linear discrete time delay systems with parametric uncertainties by matrix inequality approach the robust quadratic stability of the system is studied a control design method is developed such that the closed loop system with a cost function has a upper bound irrespective of all admissible parameter uncertainties and unknown time delays furthermore the upper bound cost can be optimized by incorporating with a minimization problem a numerical example is given to show the potential of the proposed techniques

attractors of partial differential evolution equations in an unbounded domain there is a large number of papers in which attractors of parabolic reaction diffusion equations in bounded domains are investigated in this paper these equations are considered in the whole unbounded space and a theory of attractors of such equations is built while investigating these equations specific difficulties arise connected with the noncompactness of operators with the continuity of their spectra etc therefore some new conditions on nonlinear terms arise in this paper weighted spaces are widely applied an important feature of this problem is worth mentioning namely properties of semigroups corresponding to equations with solutions in spaces of growing and of decreasing functions essentially differ

kalman filtering for continuous time uncertain systems with markovian jumping parameters studies the problem of kalman filtering for a class of uncertain linear continuous time systems with markovian jumping parameters the system under consideration is subjected to time varying norm bounded parameter uncertainties in the state and measurement equations stochastic quadratic stability of the above system is analyzed a state estimator is designed such that the covariance of the estimation error is guaranteed to be within a certain bound for all admissible uncertainties which is in terms of solutions of two sets of coupled algebraic riccati equations

stabilization of nonlinear systems under variable sampling a fuzzy control approach this paper investigates the problem of stabilization for a takagi sugeno t s fuzzy system with nonuniform uncertain sampling the sampling is not required to be periodic and the only assumption is that the distance between any two consecutive sampling instants is less than a given bound by using the input delay approach the t s fuzzy system with variable uncertain sampling is transformed into a continuous time t s fuzzy system with a delay in the state though the resulting closed loop state delayed t s fuzzy system takes a standard form the existing results on delay t s fuzzy systems cannot be used for our purpose due to their restrictive assumptions on the derivative of state delay a new condition guaranteeing asymptotic stability of the closed loop sampled data system is derived by a lyapunov approach plus the free weighting matrix technique based on this stability condition two procedures for designing state feedback control laws are given one casts the controller design into a convex optimization by introducing some over design and the other utilizes the cone complementarity linearization idea to cast the controller design into a sequential minimization problem subject to linear matrix inequality constraints which can be readily solved using standard numerical software an illustrative example is provided to show the applicability and effectiveness of the proposed controller design methodology

a note on the strong convergence towards attractors of damped forced kdv equations abstract this note is a continuation of a previous article which appeared in this journal 1988 74 369 390 in the previous work we showed that a weak dissipation is suffiient to impose a finite dimensional behavior for korteweg de vries equations with space periodic boundary conditions more precisely it was shown that all the trajectories are captured by a finite dimensional attractor however we were only able to show that the convergence of the trajectories holds good in the sense of weak topology the goal of this note is to show that in fact this convergence holds true in the sense of strong topology

mean square stabilization for sampled data t s fuzzy systems with random packet dropout this paper investigates the problem of mean square stabilization for sampled data takagi sugeno t s fuzzy networked control systems with random packet dropouts the packet dropout process is modeled as a discrete time markovian chain with complete or incomplete accessible transition probability matrix based on the lyapunov function approach sufficient conditions are derived for the mean square stability the corresponding sampled data fuzzy controller design algorithm formulated in terms of linear matrix inequalities is also given based upon the stability conditions the numerical examples and simulations are provided to illustrate the usefulness of the developed theory

asymptotic behavior of stochastic wave equations with critical exponents on mathbb r 3 the existence of a random attractor in h 1 3 x l 2 3 is proved for the damped semilinear stochastic wave equation defined on the entire space 3 the nonlinearity is allowed to have a cubic growth rate which is referred to as the critical exponent the uniform pullback estimates on the tails of solutions for large space variables are established the pullback asymptotic compactness of the random dynamical system is proved by using these tail estimates and the energy equation method

event based h filtering for sampled data systems this paper is concerned with event based h filtering for sampled data systems first an event based data packet processor is introduced to release sampled measurement outputs only if an event condition is violated as a result communication resources can be saved significantly while preserving the desired h performance second the resulting filtering error system is modeled as a system with an interval time varying delay by employing the lyapunov krasovskii functional approach a new bounded real lemma brl is established such that the filtering error system is asymptotically stable with the prescribed h performance third by performing an invertible linear transformation on the filtering error system a linear matrix inequality lmi based sufficient condition which is equivalent to the condition in the brl is obtained on the feasibility of the event based h filtering problem consequently suitable h filters and the event parameters in the event condition can be co designed provided that a set of lmis are satisfied finally a mechanical system with two masses and two springs is given to show the effectiveness of the proposed method

filtering and smoothing in an h sup infinity setting the problems of filtering and smoothing are considered for linear systems in an h sup infinity setting i e the plant and measurement noises have bounded energies are in l sub 2 but are otherwise arbitrary two distinct situations for the initial condition of the system are considered the initial condition is assumed known in one case while in the other the initial condition is not known but the initial condition the plant and measurement noise are in some weighted ball of r sup n xl sub 2 finite horizon and infinite horizon cases are considered necessary and sufficient conditions are presented for the existence of estimators both filters and smoothers that achieve a prescribed performance bound and algorithms that result in performance within the bounds are developed in case of smoothers the optimal smoother is also presented the approach uses basic quadratic optimization theory in a time domain setting as a consequence of which both linear time varying and time invariant systems can be considered with equal ease in the smoothing problem for linear time varying systems one considers only the finite horizon case

robust h sub spl infin control for linear discrete time systems with norm bounded nonlinear uncertainties this paper studies the problem of robust control of a class of uncertain discrete time systems the class of uncertain systems is described by a state space model with linear nominal parts and norm bounded nonlinear uncertainties in the state and output equations the authors address the problem of robust h sub spl infin control in which both robust stability and a prescribed h sub spl infin performance are required to be achieved irrespective of the uncertainties it has been shown that instead of the nonlinear uncertain system one may only consider a related linear uncertain system and thus a linear static state feedback control law is designed which is in terms of a riccati inequality

sliding mode control of quantized systems against bounded disturbances abstract this paper investigates the sliding mode control problem of quantized systems with simultaneous input and output disturbances in a network environment the output measurements are supposed to be quantized with a logarithmic strategy before transmitting over the digital channels the main difficulties in this design are as follows 1 there exists input output disturbances and state time delay in the plant under consideration such that model discretization is difficult to be implemented the design work is therefore forbidden to be considered in continuous time domain 2 the quantized signals piecewise constants cannot be used to synthesize a continuous time sliding mode surface 3 traditional observer technique is not effective to handle output disturbances in this paper a filtering based technique is proposed to solve these difficulties based on which a sliding mode observer based control scheme is developed to stabilize the resulting closed loop systems finally the effectiveness of the proposed methodology is illustrated via a numerical example

optimal controller for uncertain stochastic polynomial systems with deterministic disturbances this article presents the optimal quadratic gaussian controller for uncertain stochastic polynomial systems with unknown coefficients and matched deterministic disturbances over linear observations and a quadratic criterion the optimal closed form controller equations are obtained through the separation principle whose applicability to the considered problem is substantiated as intermediate results this article gives closed form solutions of the optimal regulator controller and identifier problems for stochastic polynomial systems with linear control input and a quadratic criterion the original problem for uncertain stochastic polynomial systems with matched deterministic disturbances is solved using the integral sliding mode algorithm performance of the obtained optimal controller is verified in the illustrative example against the conventional quadratic gaussian controller that is optimal for stochastic polynomial systems with known parameters and without deterministic disturbances simulation gr

robust stability criterion for discrete time uncertain markovian jumping neural networks with defective statistics of modes transitions this brief is concerned with the robust stability problem for a class of discrete time uncertain markovian jumping neural networks with defective statistics of modes transitions the parameter uncertainties are considered to be norm bounded and the stochastic perturbations are described in terms of brownian motion defective statistics means that the transition probabilities of the multimode neural networks are not exactly known as assumed usually the scenario is more practical and such defective transition probabilities comprise three types known uncertain and unknown by invoking the property of the transition probability matrix and the convexity of uncertain domains a sufficient stability criterion for the underlying system is derived furthermore a monotonicity is observed concerning the maximum value of a given scalar which bounds the stochastic perturbation that the system can tolerate as the level of the defectiveness varies numerical examples are given to verify the effectiveness of the developed results

attractors for the non autonomous nonclassical diffusion equations with fading memory abstract the long time dynamical behavior of the non autonomous nonclassical diffusion equation with fading memory when nonlinearity is critical is discussed for in the weak topological space h 0 1 l 2 r h 0 1 first the asymptotic regularity of solutions is proven and then the existence of a compact uniform attractor together with its structure and regularity is obtained while the time dependent forcing term is only translation bounded instead of translation compact the result extends and improves some results given in y xiao attractors for a nonclassical diffusion equation acta math appl sin engl ser 18 2002 273 276 c sun m yang dynamics of the nonclassical diffusion equations asympt anal 59 2008 51 81

a novel node based smoothed finite element method with linear strain fields for static free and forced vibration analyses of solids abstract this paper presents a novel node based smoothed finite element method ns fem with a higher order strain field it uses piecewise linear displacements on 3 node triangular elements together with strain field which is also linear but over the node based smoothed domains this high order strain ns fem is fundamentally different from the standard fem that uses piecewise linear displacement and constants strain fields in our high order strain ns fem the smoothed strains are expressed with complete order of polynomials which have coefficients linear and high order terms this is also different from the smoothed strain used in the existing standard ns fem which is a constant obtained by a generalized smoothing technique the unknown coefficients in assumed strain functions can be uniquely determined by linearly independent weight functions this is because the smoothed strain and compatible strain within a local region are equal in an integral sense when weighted by continuous functions we present with proofs on convergence two versions of high order strain ns fems which are termed as ns fem 1 that uses 1st order smoothed strains and ns fem 2 that uses 2nd order smoothed strains the new developed high order strain ns fem is applied for static free and forced vibration analyses of solids and our numerical results support our theorems

uniform ultimate boundedness of the solutions of uncertain dynamic delay systems with state dependent and memoryless feedback control a continuous feedback controller is developed for a class of non linear time varying uncertain systems governed by functional differential equations with retarded arguments the form of the controller guarantees that under certain assumptions all solutions are uniformly bounded in norm for time t sufficiently largo in spite of the uncertainty in system parameters and input signals furthermore given any 0 the parameters in the description of the controller can be chosen such that the closed loop solutions all satisfy x t for large t

stability and stabilization of delayed t s fuzzy systems a delay partitioning approach this paper proposes a new approach namely the delay partitioning approach to solving the problems of stability analysis and stabilization for continuous time delay takagi sugeno fuzzy systems based on the idea of delay fractioning a new method is proposed for the delay dependent stability analysis of fuzzy time delay systems due to the instrumental idea of delay partitioning the proposed stability condition is much less conservative than most of the existing results the conservatism reduction becomes more obvious with the partitioning getting thinner based on this the problem of stabilization via the so called parallel distributed compensation scheme is also solved both the stability and stabilization results are further extended to time delay fuzzy systems with time varying parameter uncertainties all the results are formulated in the form of linear matrix inequalities lmis which can be readily solved via standard numerical software the advantage of the results proposed in this paper lies in their reduced conservatism as shown via detailed illustrative examples the idea of delay partitioning is well demonstrated to be efficient for conservatism reduction and could be extended to solving other problems related to fuzzy delay systems

h sub infinity control and filtering for sampled data systems h sub infinity control and filtering problems for sampled data systems are studied necessary and sufficient conditions are obtained for the existence of controllers and filters that satisfy a specified h sub infinity performance bound when these conditions hold explicit formulas for a controller and a filter satisfying the h sub infinity performance bound are also given

bounded real lemma for linear systems with finite discrete jumps the problem of strict bounded realness for linear systems with finite discrete jumps is investigated in this paper several versions of the strict bounded real lemma for such systems in both the finite and infinite horizon cases are obtained in terms of either a riccati differential equation or riccati differential inequality with finite discrete jumps these results encompass both existing continuous time and discretetime strict bounded real lemmas

asymptotic smoothing and the global attractor of a weakly damped kdv equation on the real line abstract the existence of the global attractor of a weakly damped forced korteweg de vries equation in the phase space l 2 r is proved an optimal asymptotic smoothing effect of the equation is also shown namely that for forces in l 2 r the global attractor in the phase space l 2 r is actually a compact set in h 3 r the energy equation method is used in conjunction with a suitable splitting of the solutions the dispersive regularization properties of the equation in the context of bourgain spaces are extensively exploited

finite time synchronization of sampled data markovian jump complex dynamical networks with additive time varying delays based on dissipative theory abstract this paper is concerned with the problem of finite time synchronization issue of sampled data markovian jump complex dynamical networks mjcdns with additive time varying delays based on dissipative theory sufficient conditions to guarantee the finite time stability of mjcdns with additive time varying delays are presented sampled data control with stochastically varying sampling periods is considered the closed loop system is not just finite time bounded but also satisfies the dissipativity conditions further we handled a nonuniform sampled data controller by utilizing the properties of kronecker product combined with the appropriate lyapunov functionals technique a novel delay dependent finite time stability of dissipativity rule is derived in terms of linear matrix inequalities lmis to ensure that the delayed complex dynamical systems to be dissipative finally numerical examples are given to represent the applicability of the proposed approach

input to state stability for nonlinear systems with stochastic impulses abstract in this study the problem of input to state stability iss is systematically investigated for nonlinear systems with stochastic impulses first the iss problem is considered for systems where impulsive strengths are assumed to be stochastic and impulsive intervals are confined by the average impulsive interval then the iss problem is analyzed for nonlinear systems with both stochastic impulsive intensity and density several different cases are considered i e cases where the impulsive instants are satisfied by a renewal process poisson process semi markov chain and markov chain an example of coordination of multi agent systems is provided to illustrate the effectiveness of the proposed new stability criteria

a new model transformation of discrete time systems with time varying delay and its application to stability analysis this technical note focuses on analyzing a new model transformation of uncertain linear discrete time systems with time varying delay and applying it to robust stability analysis the uncertainty is assumed to be norm bounded and the delay intervally time varying a new comparison model is proposed by employing a new approximation for delayed state and then lifting method and simple lyapunov krasovskii functional method are used to analyze the scaled small gain of this comparison model this new approximation results in a much smaller error than the existing ones based on the scaled small gain theorem new stability criteria are proposed in terms of linear matrix inequalities moreover it is shown that the obtained conditions can be established through direct lyapunov method two numerical examples are presented to illustrate the effectiveness and superiority of our results over the existing ones

dissipativity based sampled data fuzzy control design and its application to truck trailer system this paper is concerned with the problem of dissipative control for takagi sugeno fuzzy systems under time varying sampling with a known upper bound on the sampling intervals based on the time dependent lyapunov krasovskii functional approach which makes full use of the available information about the actual sampling pattern a sufficient condition is established to guarantee the sampled data systems to be exponentially stable and strictly mathcal q mathcal s mathcal r gamma dissipative based on the criterion a design algorithm for the desired sampled data controller is proposed the effectiveness and benefits of the results developed in this paper is demonstrated by a controller design for a truck trailer system

brief paper parameter dependent robust h filtering for uncertain discrete time systems this paper is concerned with the problem of parameter dependent h filtering for discrete time systems with polytopic uncertainties the uncertain parameters are supposed to reside in a polytope being different from previous results in the quadratic framework the parameter dependent lyapunov function is used in this paper both full and reduced order filters are designed which guarantee the asymptotic stability and a prescribed h performance level the filter parameters can be obtained from the solution of convex optimization problems in terms of linear matrix inequalities which can be solved via efficient interior point algorithms numerical examples are presented to illustrate the feasibility and less conservativeness of the proposed method

brief nonlinear h filtering of sampled data systems this paper considers the problem of h filtering for nonlinear sampled data systems sufficient conditions are obtained for the existence of filters that guarantee the l 2 gain from an exogenous input to an estimation error is less than or equal to a prescribed value these conditions are expressed in terms of both continuous and discrete hamilton jacobi equations