non fragile h filtering for delayed takagisugeno fuzzy systems with randomly occurring gain variations in this study we consider a non fragile h filter design for a class of continuous time delayed takagisugeno ts fuzzy systems the filter design is assumed to include randomly occurring gain variations according to the filter s implementation two independent bernoulli distributions are employed to describe these random phenomena we focus mainly on the design of a non fragile filter so the filtering error system is asymptotically mean square stable with the prescribed h performance in the presence of both randomly occurring gain variations and a time delay a sufficient condition is developed by employing the lyapunov functional approach based on this condition an improved h filter for delayed ts fuzzy system is described which is free of randomly occurring gain variations the filter parameters are obtained by solving a set of linear matrix inequalities the effectiveness and the advantages of the proposed techniques are demonstrated by two numerical examples

robust h sup spl infin filtering for uncertain markovian jump systems with mode dependent time delays this paper considers the problem of robust h sup spl infin filtering for uncertain markovian jump linear systems with time delays which are time varying and depend on the system mode the parameter uncertainties are time varying norm bounded the aim of this problem is to design a markovian jump linear filter that ensures robust exponential mean square stability of the filtering error system and a prescribed l sub 2 induced gain from the noise signals to the estimation error for all admissible uncertainties a sufficient condition for the solvability of this problem is obtained the desired filter can be constructed by solving a set of linear matrix inequalities an illustrative numerical example is provided to demonstrate the effectiveness of the proposed approach

robust h filtering for sampled data fuzzy systems abstract this paper is concerned with robust h filtering for takagi sugeno sampled data fuzzy systems with uncertain parameters takagi sugeno fuzzy system can describe a wide class of nonlinear systems and is widely used in many engineering fields recently system analysis and control design for nonlinear systems based fuzzy system approach have been active the system is usually modelled as a continuous time system while in practical situations the observation is taken at discrete instants such an observation can be represented as a delayed signal first it is shown that the error system which stems from an original fuzzy system and a sampled data filter becomes a system with time varying delay sufficient conditions for the error system to achieve the robust stability with h disturbance attenuation are given in terms of linear matrix inequalities lmis we derive such conditions via output delay system approach under the assumption that sampling time is not greater than some prescribed number based on such conditions we propose a robust h sampled data filter design for a fuzzy system we consider two different cases for the premise variables in our filter design numerical examples are given to illustrate our robust h sampled data filtering

stability analysis and performance design for fuzzy model based control system under imperfect premise matching this paper investigates the stability analysis and performance design of nonlinear systems to facilitate the stability analysis the takagi sugeno t s fuzzy model is employed to represent the nonlinear plant under the imperfect premise matching in which t s fuzzy model and fuzzy controller do not share the same membership functions a fuzzy controller with enhanced design flexibility and robustness property is proposed to control the nonlinear plant however the nice characteristic given by the perfect premise matching leading to conservative stability conditions vanishes in this paper under the imperfect premise matching information of membership functions of the fuzzy model and controller are considered in stability analysis with the introduction of slack matrices relaxed linear matrix inequality lmi based stability conditions are derived using lyapunov based approach furthermore lmi based performance conditions are provided to guarantee system performance simulation examples are given to illustrate the effectiveness of the proposed approach

sampled data h fuzzy filtering for nonlinear systems with missing measurements in this paper a sampled data h fuzzy filtering problem is considered for nonlinear systems with missing measurements the nonlinear sampled data system and missing measurements are assumed to be represented by a takagisugeno ts fuzzy system and an independent identically distributed bernoulli random process respectively based on the fuzzy system the h fuzzy filtering problem is formulated to design the sampled data fuzzy filter by using the exponential mean square stability definition the stability condition with an h performance is guaranteed for the fuzzy system with the sampled data fuzzy filter and its sufficient condition is converted into the linear matrix inequality lmi format finally an example is provided to verify the effectiveness of the proposed fuzzy filtering technique

robust h filtering for nonlinear systems abstract a robust or h approach to filtering for nonlinear systems is considered a bound on the estimate error as a function of the disturbance energy is obtained the corresponding dynamic programming equation is a first order pde this has computational ramifications the case where the measurements are discrete time is considered also a numerical method is discussed

sampled data observer based output feedback fuzzy stabilization of nonlinear systems exact discrete time design approach this paper presents a new direct discrete time design methodology of a sampled data observer based output feedback fuzzy controller for a class of nonlinear system that is exactly modeled in takagi sugeno s form at least locally a fundamental yet challenging issue in this direction is the unavailability of the exact discrete time model of the nonlinear plant in a closed form in contrast to the earlier works that are based on an approximate discrete time model thus the stability obtained in the design step is not preserved in the implementation step we employ an exact discrete time fuzzy model in an integral form sufficient asymptotic stabilization conditions are investigated in the discrete time lyapunov sense we then show that the resulting sampled data controller indeed asymptotically stabilizes the nonlinear plant an example is provided to illustrate the effectiveness of the proposed methodology

on regional nonlinear h filtering the structure of the nonlinear h filter in the neighborhood of the estimated trajectory is investigated and a bound on the size of the neighborhood that allows this structure is determined both for finite and infinite horizons riccati inequalities that depend on the estimated trajectory are derived for finding the filter gain matrix and an algorithm for calculating the bound on the size of the above neighborhood is presented explicit formulas are obtained in the infinite horizon case for the minimum achievable disturbance attenuation level the size of the neighborhood and the corresponding filter gain

h filtering of discrete time fuzzy systems via basis dependent lyapunov function approach this paper is concerned with the h filtering problem for a class of discrete time fuzzy systems attention is focused on the design of a stable filter guaranteeing a prescribed noise attenuation level in the h sense by using basis dependent lyapunov functions sufficient conditions for the solvability of this problem are obtained it has been shown that the h filtering problem can be solved as a linear matrix inequality lmi optimization problem two examples are provided to demonstrate the applicability of the proposed approach

fuzzy stabilization of nonlinear systems under sampled data feedback an exact discrete time model approach this paper addresses stabilization problems for a nonlinear system via a sampled data fuzzy controller the nonlinear system is assumed to be exactly modeled in takagi sugeno s form at least locally unlike the conventional direct discrete time design approach based on an approximate discrete time model the sampled data fuzzy controllers are designed based on an exact discrete time model sufficient design conditions are formulated in terms of linear matrix inequalities it is shown that whenever the exact discrete time fuzzy model is asymptotically stabilizable via the sampled data fuzzy controller uniformly bounded in the state then so is the original nonlinear system a numerical example is given to illustrate the effectiveness of the proposed methodology

image compression using adaptive vector quantization the paper demonstrates the application of adaptive vector quantization techniques to the coding of monochromatic and color pictures codebooks of representative vectors are generated for different portions of the image by means of extensive simulations the performance of the coder for monochrome images is estimated as a function of the various coding parameters vector dimensionality number of representative vectors and degree of adaptivity it is shown that for a vector size of dimension 4 there is a zone of operation ranging from 1 0 to 1 5 bits pixel where adaptive vector quantization is advantageous despite the simplicity of the decoder the performance of the adaptive vector quantizer is found to be comparable with block transform coding schemes for both monochrome and color pictures

robust h sub spl infin filtering for stochastic time delay systems with missing measurements in this paper the robust hinfin filtering problem is studied for stochastic uncertain discrete time delay systems with missing measurements the missing measurements are described by a binary switching sequence satisfying a conditional probability distribution we aim to design filters such that for all possible missing observations and all admissible parameter uncertainties the filtering error system is exponentially mean square stable and the prescribed hinfin performance constraint is met in terms of certain linear matrix inequalities lmis sufficient conditions for the solvability of the addressed problem are obtained when these lmis are feasible an explicit expression of a desired robust hinfin filter is also given an optimization problem is subsequently formulated by optimizing the hinfin filtering performances finally a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach

image sequence coding using vector quantization in this paper a new interframe coding technique based upon vector quantization is presented this algorithm has as its basis twodimensional block vector quantization at the frame level onto which is grafted the concept of adaptive codebook replenishment and frame replenishment this algorithm includes three strategies label replenishment label replenishment with mean shift and label replenishment with mean shift and selective codeword replacement the last two strategies efficiently update the codebook to track the changes in local statistics on a frame basis compared with three dimensional block vector quantization 16 for bit rates between 0 5 and 0 65 the normalized mean squared error nmse is reduced by a factor ranging between 2 and 2 5 by the use of replenishment

h sub 2 and h sub spl infin robust filtering for convex bounded uncertain systems investigates robust filtering design problems in h sub 2 and h sub spl infin spaces for continuous time systems subjected to parameter uncertainty belonging to a convex bounded polyhedral domain it is shown that by a suitable change of variables both designs can be converted into convex programming problems written in terms of linear matrix inequalities the results generalize the ones available in the literature to date in several directions first all system matrices can be corrupted by parameter uncertainty and the admissible uncertainty may be structured then assuming the order of the uncertain system is known the optimal guaranteed performance h sub 2 and h sub spl infin filters are proven to be of the same order as the order of the system a numerical example illustrate the theoretical results

technical communique further studies on lmi based relaxed stabilization conditions for nonlinear systems in takagi sugeno s form this paper further studies stabilization of nonlinear systems represented by a takagi sugeno t s discrete fuzzy model by extending a nonquadratic lyapunov function and applying a nonparallel distributed compensation non pdc law a new stabilization conclusion is presented that is a generalization of some previous results in the literature the new conclusion under a special situation is also suitable for a pdc law which presents to be more relaxed than some existing results an example is provided to demonstrate the effectiveness of the new conclusions

decentralized h fuzzy filter for nonlinear large scale sampled data systems with uncertain interconnections abstract this paper proposes a decentralized h fuzzy filter technique for nonlinear large scale interconnected systems that are based on the takagi sugeno fuzzy model the large scale system has unknown interconnection terms that are assumed to satisfy the quadratic bounds an error system between the nonlinear large scale system and the decentralized filter is constructed by using the fuzzy lyapunov technique sufficient conditions are proposed for both showing asymptotic stability and guaranteeing h fuzzy filter performance these sufficient conditions are derived in terms of linear matrix inequalities finally simulation examples are given to demonstrate the effectiveness of the proposed technique

a novel approach to h_ bm infty decentralized fuzzy observer based fuzzy control design for nonlinear interconnected systems in general due to the interactions among subsystems it is difficult to design an h infin decentralized output feedback controller for nonlinear interconnected systems this study introduces h infin decentralized fuzzy observer based fuzzy control design where the premise variables depend on the state variables estimated by a fuzzy observer for nonlinear interconnected systems via t s fuzzy models the fuzzy control design for this case is more flexible but much more complex than that for the case where the premise variables depend on the state variables only a novel decoupled method is proposed in this study to transform the non linear matrix inequality non lmi conditions into some lmi forms by the proposed decoupled method the problem of h infin decentralized fuzzy observer based fuzzy control design for nonlinear interconnected systems is characterized in terms of solving an eigenvalue problem evp with five prespecified scalars for each subsystem in general it is a difficult task to solve the evp with five prespecified scalars fortunately this special evp can be easily solved by using a genetic algorithm and an lmi based optimization method finally a simulation example is given to illustrate the design procedure and robust performance of the proposed methods

progressive image transmission by transform coefficient residual error quantization a progressive image transmission scheme based on iterative transform coding structure is proposed for application in interactive image communication over low bandwidth channels the scheme not only provides progressive transmission but also guarantees lossless reproduction combined with a degree of compression the image to be transmitted undergoes an orthogonal transform and the transform coefficients are quantized scalar or vector before transmission the novelty is that the residual error array due to quantization is iteratively fedback and requantized scalar or vector the coded residual error information is progressively transmitted and utilized in reconstructing the successive approximations it is shown that the average reconstruction error variance converges to zero as the number of iterative stages approaches infinity in practice lossless reproduction can be achieved with a small number of iterations by using an entropy coder on the final residual error image computer simulation results demonstrate the effectiveness of the technique

a new fuzzy lyapunov function for relaxed stability condition of continuous time takagi sugeno fuzzy systems this paper presents a new fuzzy lyapunov function flf for the stability analysis of continuous time takagi sugeno t s fuzzy systems unlike conventional flfs the proposed one depends not only on the fuzzy weighting functions of the t s fuzzy systems but on their first order time derivatives as well based on the proposed flf a sufficient stability condition is derived in the form of linear matrix inequalities depending on the upper bounds on the second order time derivative of the fuzzy weighting functions as well as the first order ones finally some examples demonstrate that the proposed condition can provide less conservative results than the previous ones in the literature

to transmit or not to transmit a discrete event triggered communication scheme for networked takagi sugeno fuzzy systems this paper first proposes a discrete event triggered communication scheme for a class of networked takagi sugeno t s fuzzy systems this scheme has two main features 1 whether or not the sampled state should be transmitted is determined by the current sampled state and the error between the current sampled state and the latest transmitted state compared with those in a periodic time triggered communication scheme the communication bandwidth utilization is considerably reduced while preserving the desired control performance and 2 it is a discrete event triggered communication scheme due to the fact that the triggered conditions are only measured and checked at a constant sampling period compared with a continuous event triggered communication scheme the special hardware for continuous measurement and computation is no longer needed second a networked t s fuzzy model is delicately constructed which not only considers nonuniform time scales in the networked t s fuzzy model and the parallel distributed compensation fuzzy control rules but includes the aforementioned state error as well third a stability criterion and a stabilization criterion about the networked t s fuzzy system are derived respectively the stability criterion and stabilization criterion can provide a tradeoff to balance the required communication resource and the desired performance lowering the desired performance allows the network to allocate more limited bandwidth to other nodes in need finally a numerical example is given to show the effectiveness of the proposed method

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

process algebra for performance evaluation this paper surveys the theoretical developments in the field of stochastic process algebras process algebras where action occurrences may be subject to a delay that is determined by a random variable a huge class of resource sharing systems like large scale computers client server architectures networks can accurately be described using such stochastic specification formalisms the main emphasis of this paper is the treatment of operational semantics notions of equivalence and sound and complete axiomatisations of these equivalences for different types of markovian process algebras where delays are governed by exponential distributions starting from a simple actionless algebra for describing time homogeneous continuous time markov chains we consider the integration of actions and random delays both as a single entity like in known markovian process algebras like tipp pepa and empa and as separate entities like in the timed process algebras timed csp and tccs in total we consider four related calculi and investigate their relationship to existing markovian process algebras we also briefly indicate how one can profit from the separation of time and actions when incorporating more general non markovian distributions

non quadratic local stabilization for continuous time takagi sugeno models this paper is concerned with non quadratic stabilization of continuous time takagi sugeno ts models the well known problem of handling time derivatives of membership functions mfs as to obtain conditions in the form of linear matrix inequalities lmis is overcome by reducing global goals to the estimation of a region of attraction instead of parallel distributed compensation pdc a non pdc control law is proposed according to the non quadratic nature of the lyapunov function examples are provided to show the advantages over the quadratic and some non quadratic approaches

delay dependent robust h sub spl infin and l sub 2 l sub spl infin filtering for a class of uncertain nonlinear time delay systems this note presents delay dependent robust h sub spl infin and l sub 2 l sub spl infin filter designs for a class of nonlinear systems with multiple time varying delays in the state and parameter uncertainties residing in a polytope the nonlinearities are assumed to satisfy global lipschitz conditions attention is focused on the design of robust full order and reduced order filters guaranteeing a prescribed noise attenuation level in an h sub spl infin or l sub 2 l sub spl infin sense the admissible filters 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

an improved result on the stability of uncertain t s fuzzy systems with interval time varying delay this paper is concerned with the stability of uncertain t s fuzzy systems with interval time varying delay by uniformly dividing the delay interval into multiple segments and constructing an appropriate augmented lyapunov krasovskii functional some less conservative stability criteria are obtained which include some existing results as special cases since a tighter bounding inequality is employed to deal with time varying delay dependent integral items then some sources of computational complexity such as the general convex combination and free weighting matrices are not necessary to be adopted in the derivation of our results as a result the developed criteria not only theoretically improve some existing results but also have higher computational efficiency numerical examples are given to demonstrate the effectiveness of the proposed method

h sub spl infin filtering for fuzzy singularly perturbed systems with pole placement constraints an lmi approach this paper addresses the problem of designing an h sub spl infin filter for a class of nonlinear singularly perturbed systems described by a takagi sugeno ts fuzzy model based on a linear matrix inequality lmi approach we develop a fuzzy h sub spl infin controller that guarantees that i the l sub 2 gain from an exogenous input to a filter error is less than or equal to a prescribed value and ii the poles of each local filter are within a prespecified region in order to alleviate the ill conditioning resulting from the interaction of slow and fast dynamic modes solutions to the problem are given in terms of linear matrix inequalities which are independent of the singular perturbation spl epsiv when spl epsiv is sufficiently small the proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard but also to nonstandard singularly perturbed nonlinear systems a numerical example is provided to illustrate the design developed in this paper

a multiple lyapunov function approach to stabilization of fuzzy control systems this paper addresses stability analysis and stabilization for takagi sugeno fuzzy systems via a so called fuzzy lyapunov function which is a multiple lyapunov function the fuzzy lyapunov function is defined by fuzzily blending quadratic lyapunov functions based on the fuzzy lyapunov function approach we give stability conditions for open loop fuzzy systems and stabilization conditions for closed loop fuzzy systems to take full advantage of a fuzzy lyapunov function we propose a new parallel distributed compensation pdc scheme that feedbacks the time derivatives of premise membership functions the new pdc contains the ordinary pdc as a special case a design example illustrates the utility of the fuzzy lyapunov function approach and the new pdc stabilization method

robust nonfragile h_ infty filtering of fuzzy systems with linear fractional parametric uncertainties this paper is concerned with the h filtering problem for continuous time takagi sugeno t s fuzzy systems different from existing results for fuzzy h filtering the proposed ones are toward uncertain fuzzy systems with linear fractional parametric uncertainties attention is focused on the design of a fuzzy filter such that the filtering error system preserves a prescribed h performance where the filter to be designed is assumed to have gain variations by a descriptor representation approach two sufficient conditions for the h filter design are proposed in terms of linear matrix inequalities lmis when these lmis are feasible an explicit expression of the desired filter is given a simulation example will be given to show the efficiency of the proposed methods

finite time synchronization of sampled data t s fuzzy complex dynamical networks subject to average dwell time approach abstract the problem of finite time synchronization for takagi sugeno t s fuzzy complex dynamical networks with coupling delays via sampled data control is presented in this paper to change the sampled data control system into a continuous time delayed system an input delay approach is applied based on the lyapunov stability theory a suitable lyapunov krasovskii functional lkf is constructed with the kronecker products furthermore by applying the average dwell time approach a novel sufficient condition is established to ascertain the finite time stabilization of fuzzy complex dynamical networks cdns with switching signals the proposed method is less conservative than conventional approaches since the newly developed time dependent fuzzy lkf is used the proposed sufficient condition can be represented in the form of linear matrix inequalities lmis finally the effectiveness and superiority of the proposed approach is validated through both numerical and practical examples

block transform image coding by multistage vector quantization with optimal bit allocation a multistage vector quantization with optimal bit allocation mvq oba in the transform domain is presented a set of bit allocation planes is first obtained by slicing a scalar optimal bit allocation map where the number of bits assigned to each coefficient is proportional to the coefficient variance the set of bit allocation planes determines the coefficients to be used and the codebook size at each stage the vector dimensionalities are restricted to small values and relatively small codebooks are used thus reducing both the overhead required for transmitting the codebooks and the complexity in codebook design the computer simulation results demonstrate that mvq oba is competitive with many other transform coding techniques including variable length transform coding mvq oba is well suited for progressive transmission

robust h sub spl infin filtering for nonlinear stochastic systems this paper describes the robust h sub spl infin filtering analysis and synthesis of nonlinear stochastic systems with state and exogenous disturbance dependent noise we assume that the state and measurement are corrupted by stochastic uncertain exogenous disturbance and that the system dynamic is modeled by ito spl circ type stochastic differential equations for general nonlinear stochastic systems the h sub spl infin filter can be obtained by solving second order nonlinear hamilton jacobi inequalities when the worst case disturbance is considered in the design procedure a mixed h sub 2 h sub spl infin filtering problem is also solved by minimizing the total estimation error energy it is found that for a class of special nonlinear stochastic systems the h sub spl infin filtering design can be given via solving several linear matrix inequalities instead of hamilton jacobi inequalities a few examples show that the proposed methods are effective