h_ infty filtering for nonlinear discrete time systems subject to quantization and packet dropouts this paper investigates the problem of h filtering for a class of nonlinear discrete time systems with measurement quantization and packet dropouts each output is transmitted via an independent communication channel and the phenomenon of packet dropouts in transmission is governed by an individual random binary distribution while the quantization errors are treated as sector bound uncertainties based on a piecewise lyapunov function an approach to the design of h piecewise filter is pro posed such that the filtering error system is stochastically stable with a guaranteed h performance some slack matrices are introduced to facilitate the filter design procedure by eliminating the coupling between the lyapunov matrices and the system matrices the filter parameters can be obtained by solving a set of linear matrix inequalities lmis which are numerically tractable with commercially available software finally two illustrative examples are provided to show the effectiveness of the proposed method

stochastic decision making in the minority game abstract a discussion is presented of the effects of stochasticity in the decision making of agents in the minority game both simulational and analytic results are reported and discussed for both additive and multiplicative noise as a function of the ratio d of information dimension to number of agents a phase transition separates a low d non ergodic phase from a high d ergodic phase for additive noise the critical dc is temperature independent but for multiplicative noise dc t decreases with t additive noise does not affect the asymptotic behaviour for d dc but is relevant below dc multiplicative noise has consequence for all d

h filtering for fuzzy systems with immeasurable premise variables an uncertain system approach this paper discusses a design of stable filters with h disturbance attenuation of takagi sugeno fuzzy systems with immeasurable premise variables when we consider the filter design of takagi sugeno fuzzy systems the selection of premise variables plays an important role if the premise variable is the state of the system then a fuzzy system describes a wide class of nonlinear systems in this case however a filter design of fuzzy systems based on parallel distributed compensator idea is infeasible to avoid such a difficulty we consider the premise variables uncertainties then we consider a robust h filtering problem for such an uncertain system a solution of the problem is given in terms of linear matrix inequalities lmis some numerical examples are given to illustrate our theory

robust h sub spl infin and mixed h sub 2 h sub spl infin filters for equalization designs of nonlinear communication systems fuzzy interpolation approach generally it is difficult to design equalizers for signal reconstruction of nonlinear communication channels with uncertain noises in this paper we propose the h sub spl infin and mixed h sub 2 h sub spl infin filters for equalization detection of nonlinear channels using fuzzy interpolation and linear matrix inequality lmi techniques first the signal transmission system is described as a state space model and the input signal is embedded in the state vector such that the signal reconstruction estimation design becomes a nonlinear state estimation problem then the takagi sugeno fuzzy linear model is applied to interpolate the nonlinear channel at different operation points through membership functions since the statistics of noises are unknown the fuzzy h sub spl infin equalizer is proposed to treat the state estimation problem from the worst case robust point of view when the statistics of noises are uncertain but with some nominal or average information available the mixed h sub 2 h sub spl infin equalizer is employed to take the advantage of both h sub 2 optimal performance with nominal statistics of noises and the h sub spl infin robustness performance against the statistical uncertainty of noises using the lmi approach the fuzzy h sub 2 h sub spl infin equalizer detector design problem is characterized as an eigenvalue problem evp the evp can be solved efficiently with convex optimization techniques

minority games diversity cooperativity and the concept of intelligence abstract in this paper we revisit some minority games formed by two different types of agents there are some games where the differences of power processing among the agents are fundamental for achieving success in other games which are characterized by a dynamical phase transition the results can only be explained by cooperative intelligence and diversity in both cases the concept of informational efficiency plays an important role in the understanding of the dynamics finally aiming to explain the results of these games we try to make a link among diversity informational efficiency and the concept of intelligence

nonquadratic stabilization conditions for a class of uncertain nonlinear discrete time ts fuzzy models a new approach the discrete time uncertain nonlinear models are considered in a takagi sugeno form and their stabilization is studied through a non quadratic lyapunov function the classical conditions consider a one sample variation here the main results are obtained considering k samples variation i e deltak v x t v x t k v x t the results are shown to always include the classical cases and several examples illustrate the effectiveness of the approach

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

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

new results on h_ infty filter design for nonlinear systems with time delay via t s fuzzy models this paper focuses on the problem of designing h filters for nonlinear systems with time varying delay via takagi sugeno t s fuzzy models some new results on h filter design are proposed by estimating the upper bounds of the derivatives of lyapunov functionals without ignoring some useful terms which improve the existing ones in addition a sufficient condition for the existence of such an h filter is established in terms of solutions to a set of linear matrix inequalities lmis finally two examples are given to demonstrate the effectiveness of the proposed method

lmi based stability analysis for fuzzy model based control systems using artificial t s fuzzy model this paper investigates the stability of fuzzy model based fmb control systems an alternative stability analysis approach using an artificial fuzzy system based on the lyapunov stability theory is proposed to facilitate the stability analysis the continuous membership functions of the takagi sugeno t s fuzzy model are represented by the staircase ones with the nice property of the staircase membership functions it turns the set of infinite number of linear matrix inequality lmi based stability conditions into a finite one furthermore the staircase membership functions carrying system information can be brought to the stability conditions to relax the stability conditions the stability of the original fmb control systems is guaranteed by the satisfaction of the lmi based stability conditions the proposed stability analysis is applied to the fmb control systems of which the t s fuzzy model and fuzzy controller do not share the same premise membership functions and thus is able to enhance the design flexibility of the fuzzy controller a simulation example is given to illustrate the merits of the proposed approach

robust h sub spl infin disturbance attenuation for a class of uncertain discrete time fuzzy systems the paper is concerned with robust stabilization and h sub spl infin control of a class of uncertain discrete time fuzzy systems the class of uncertain systems is described by state space takagi sugeno ts fuzzy models with linear nominal parts and norm bounded parameter uncertainties in the state and output equations first a sufficient condition on robust stability of the fuzzy models is proposed then h sub spl infin disturbance attenuation performance of the fuzzy models is analyzed some sufficient conditions are derived on robust h sub spl infin disturbance attenuation in which both robust stability and a prescribed h sub spl infin performance are required to be achieved irrespective of the uncertainties a numerical example shows the use of the results on the stabilization and h sub spl infin disturbance attenuation of a class of discrete time nonlinear systems via fuzzy switch

nonfragile h_ infty filtering of continuous time fuzzy systems this paper is concerned with the problem of nonfragile h filtering for a class of continuous time fuzzy systems attention is focused on the design of a 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 using the quadratic lyapunov function approach and adding slack matrix variables sufficient conditions for designing the nonfragile h filter are proposed in terms of solutions to a set of linear matrix inequalities lmis finally a simulation example will be given to show the efficiency of the proposed design methods

stability and stabilization of t s fuzzy systems with two additive time varying delays abstract in this paper new stability and stabilization conditions are proposed for a novel t s fuzzy system the novel t s fuzzy model considered contains two additive time varying delays and has strong application background in networked control systems in contrast to earlier models new lyapunov krasovskii functionals and integral inequalities are used to investigate these criteria as a result new stability and stabilization conditions involving two delay components are established in terms of linear matrix inequalities numerical examples are provided to demonstrate the effectiveness of the criteria

l sub 2 optimal filter reduction a closed loop approach this paper is concerned with the problem of order reduction of a full order kalman filter for a stable linear signal model so that the steady state filtering error variance associated with the reduced order filter is minimized by an orthogonal parameterization the above problem is formulated to minimize the filtering error variance over a set of orthogonal matrices both continuous and iterative algorithms are derived to compute an optimal reduced order filter the algorithms are shown to possess good properties including the desirable convergence property the proposed algorithms are simple and effective numerical examples are presented to demonstrate the effectiveness and the significant advantages of the proposed algorithms over the existing open loop methods such as the well known balanced truncation method

minority game with sk interactions a batch minority game with fake random history and additional sk like quenched interaction is introduced and analysed a mixing parameter quantifies the admixture and dictates the relative dominance of the two contributions if 0 agent decisions are based on their strategies and point scores alone as in the pure minority game whereas for 0 the agents also communicate with each other directly and update their points accordingly keeping the minority game dynamics in which the agents points are updated in parallel at each time step the aim is to understand what happens if instead of simply using the normal strategy based decisions the agents also take account of an effective field generated by the other agents it is shown that the sk interaction introduces a noise term which is broader than that in the normal minority game and which furthermore kills the normal phase transition it is also shown that the same effect would occur if instead of an sk interaction gaussian distributed quenched random fields are added by calculating order parameters in the time translational invariant phase we show that the system is persistent in a ergodic phase both simulational and analytical results are presented

evolution equation of phenotype distribution general formulation and application to error catastrophe an equation describing the evolution of phenotypic distribution is derived using methods developed in statistical physics the equation is solved by using the singular perturbation method and assuming that the number of bases in the genetic sequence is large applying the equation to the mutation selection model by eigen provides the critical mutation rate for the error catastrophe phenotypic fluctuation of clones individuals sharing the same gene is introduced into this evolution equation with this formalism it is found that the critical mutation rate is sometimes increased by the phenotypic fluctuations i e noise can enhance robustness of a fitted state to mutation our formalism is systematic and general while approximations to derive more tractable evolution equations are also discussed

non fragile asynchronous h control for uncertain stochastic memory systems with bernoulli distribution abstract this study constructs and investigates the non fragile asynchronous h control for uncertain stochastic memory systems with bernoulli distribution the system not only contains the randomly occurring uncertainties of all parameters rouaps and stochastic disturbances in the system model but also includes randomly gain perturbations in the controller by introducing the stochastic variables a new model structure is built obeying bernoulli distribution to describe the system and the controller moreover a modified lyapunov krasovskii function lkf is constructed combining ito s differential formula and free weighting matrix method less conservative results are presented in terms of the linear matrix inequality lmi furthermore an observer based non fragile asynchronous h controller is designed without any limits on the system parameters finally three numerical examples are provided to demonstrate the effectiveness and feasibility of the proposed results

brief paper non fragile h filter design for linear continuous time systems this paper studies the problem of non fragile h filter design for linear continuous time systems the filter to be designed is assumed to include additive gain variations which result from filter implementations a notion of structured vertex separator is proposed to approach the problem and exploited to develop sufficient conditions for the non fragile h filter design in terms of solutions to a set of linear matrix inequalities lmis the designs guarantee the asymptotic stability of the estimation errors and the h performance of the system from the exogenous signals to the estimation errors below a prescribed level a numerical example is given to illustrate the effect of the proposed method

h_ infty filter design for a class of networked control systems via t s fuzzy model approach this paper is concerned with h design for a class of networked control systems ncss with multiple state delays via the takagi sugeno t s fuzzy model the transfer delays and packet loss that are induced by the limited bandwidth of communication networks are considered the focus of this paper is on the analysis and design of a full order h filter such that the filtering error dynamics are stochastically stable and a prescribed h attenuation level is guaranteed sufficient conditions are established for the existence of the desired filter in terms of linear matrix inequalities lmis an example is given to illustrate the effectiveness and applicability of the proposed design method

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

statistical mechanics of socio economic systems with heterogeneous agents we review the statistical mechanics approach to the study of the emerging collective behaviour of systems of heterogeneous interacting agents the general framework is presented through examples in such contexts as ecosystem dynamics and traffic modelling we then focus on the analysis of the optimal properties of large random resource allocation problems and on minority games and related models of speculative trading in financial markets discussing a number of extensions including multi asset models majority games and models with asymmetric information finally we summarize the main conclusions and outline the major open problems and limitations of the approach

a descriptor representation approach to observer based h control synthesis for discrete time fuzzy systems this work is concerned with the observer based h control synthesis problem of discrete time takagi sugeno t s fuzzy systems with external disturbances the objective is to find a new way to design the controller and observer guaranteeing a prescribed h performance of the fuzzy system by the descriptor representation approach two new conditions for observer based h control synthesis are proposed based on various lyapunov function candidates which are in the form of linear matrix inequalities lmis a numerical example will be given to show the efficiency of the proposed method

theory of networked minority games based on strategy pattern dynamics we formulate a theory of agent based models in which agents compete to be in a winning group the agents may be part of a network or not and the winning group may be a minority group or not an important feature of the present formalism is its focus on the dynamical pattern of strategy rankings and its careful treatment of the strategy ties which arise during the system s temporal evolution we apply it to the minority game with connected populations expressions for the mean success rate among the agents and for the mean success rate for agents with k neighbors are derived we also use the theory to estimate the value of connectivity p above which the binary agent resource system with high resource levels makes the transition into the high connectivity state

three phases of the minority game we define three phases of the minority game according to the value 2m n 2m n the ratio of the number of entries in a strategy to the number of agents the time sequence of the population in one room has distinct feature in different phase it shows quasi periodic structure in the first phase where c2 c2 the system is able to reach its best performance in reducing the population variance the crucial factor which hinders the system to reach its best performance in the first and second phases is the number of agents who switch strategy at the same time when c2 c2 the constraint that bound 2m predictions in a strategy is small so that too many agents will switch to a better strategy simultaneously as a result they form a majority group and are more likely to lose we give analytical approximate formulas for the population variance in the first and third phases we have also determined the phase changing point c1 c1

fuzzy regulators and fuzzy observers relaxed stability conditions and lmi based designs this paper presents new relaxed stability conditions and lmi linear matrix inequality based designs for both continuous and discrete fuzzy control systems they are applied to design problems of fuzzy regulators and fuzzy observers first takagi and sugeno s fuzzy models and some stability results are recalled to design fuzzy regulators and fuzzy observers nonlinear systems are represented by takagi sugeno s ts fuzzy models the concept of parallel distributed compensation is employed to design fuzzy regulators and fuzzy observers from the ts fuzzy models new stability conditions are obtained by relaxing the stability conditions derived in previous papers lmi based design procedures for fuzzy regulators and fuzzy observers are constructed using the parallel distributed compensation and the relaxed stability conditions other lmi s with respect to decay rate and constraints on control input and output are also derived and utilized in the design procedures design examples for nonlinear systems demonstrate the utility of the relaxed stability conditions and the lmi based design procedures

a new lmi based approach to relaxed quadratic stabilization of t s fuzzy control systems this paper proposes a new quadratic stabilization condition for takagi sugeno t s fuzzy control systems the condition is represented in the form of linear matrix inequalities lmis and is shown to be less conservative than some relaxed quadratic stabilization conditions published recently in the literature a rigorous theoretic proof is given to show that the proposed condition can include previous results as special cases in comparison with conventional conditions the proposed condition is not only suitable for designing fuzzy state feedback controllers but also convenient for fuzzy static output feedback controller design the latter design work is quite hard for t s fuzzy control systems based on the lmi based conditions derived one can easily synthesize controllers for stabilizing t s fuzzy control systems since only a set of lmis is involved the controller design is quite simple and numerically tractable finally the validity and applicability of the proposed approach are successfully demonstrated in the control of a continuous time nonlinear system

a modified crow kimura evolution model with reduced fitness for the smooth distribution of population abstract we investigate an evolution model in which the fitness depends on the steepness of population distribution via hamming classes the absolute value of the logarithm of the probability ratios for the neighbor hamming classes the model has a rather rich phase structure with observed oscillations of the mean fitness in the dynamics specifically the fitness is reduced compared to the standard crow kimura model when the steepness is less than a certain value d we compare the mean fitness of our model with the mean fitness of crow kimura model with the same parameters our work reveals that there is a threshold value d c for which d d c there are no oscillations of the mean fitness and it is less than the corresponding fitness in the crow kimura model with the same parameters for d d c the mean fitness oscillates with time the time averaged mean fitness is identical to the mean fitness in crow kimura model and there is a wider distribution than in the case of crow kimura model this is a significant advantage in dynamic environment

a new approach to robust and non fragile h control for uncertain fuzzy systems this paper investigates the robust h control and non fragile control problems for takagi sugeno t s fuzzy systems with linear fractional parametric uncertainties the robust h control problem is to design a state feedback controller such that the robust stability and a prescribed h performance of the resulting closed loop system is ensured and the non fragile h control problem is to design a state feedback controller with parameter uncertainties based on the linear matrix inequality lmi approach new sufficient conditions for the solvability of the two problems are obtained it is shown that the desired state feedback fuzzy controller can be constructed by solving a set of lmis numerical examples are also provided to demonstrate the effectiveness of the proposed design method

dynamics of the batch minority game with inhomogeneous decision noise we study the dynamics of a version of the batch minority game with random external information and with different types of inhomogeneous decision noise additive and multiplicative using generating functional techniques a la de dominicis the control parameters in this model are the ratio ensuremath alpha p n of the number p of possible values for the external information over the number n of trading agents and the statistical properties of the agents decision noise parameters the presence of decision noise is found to have the general effect of damping macroscopic oscillations which explains why in certain parameter regions it can effectively reduce the market volatility as observed in earlier studies in the limit n ensuremath rightarrow ensuremath infty we i solve the first few time steps of the dynamics for any ensuremath alpha ii calculate the location ensuremath alpha c of the phase transition signaling the onset of anomalous response and iii solve the statics for ensuremath alpha g ensuremath alpha c we find that ensuremath alpha c is not sensitive to additive decision noise but we arrive at nontrivial phase diagrams in the case of multiplicative noise our theoretical results find excellent confirmation in numerical simulations

on energy to peak filtering for nonuniformly sampled nonlinear systems a markovian jump system approach this paper focuses on the filter design for nonuniformly sampled nonlinear systems which can be approximated by takagi sugeno t s fuzzy systems the sampling periods of the measurements are time varying and the nonuniform observations of the outputs are modeled by a homogenous markov chain a mode dependent estimator with a fast sampling frequency is proposed such that the estimation can track the signal to be estimated with the nonuniformly sampled outputs the nonlinear systems are discretized with the fast sampling period by using an augmentation technique the corresponding stochastic estimation error system is obtained by studying the stochastic stability and the energy to peak performance of the estimation error system we derive the linear matrix inequality based sufficient conditions the parameters of the mode dependent estimator can be calculated by using the proposed iterative algorithm two examples are used to demonstrate the design procedure and the efficacy of the proposed design 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

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

finite time h fuzzy control of nonlinear markovian jump delayed systems with partly uncertain transition descriptions abstract this paper addresses a finite time h fuzzy control problem for a class of nonlinear markovian jump delayed systems with partly uncertain transition descriptions which is represented as a takagi sugeno t s fuzzy model a new homogeneous polynomial of partly uncertain transition rates is chosen free matrix based and double integral forms of the wirtinger based integral inequalities are employed to make the proposed approach less conservative then sufficient conditions are derived such that the fuzzy nonlinear makovian jump delayed system exhibits stochastic finite time boundedness finally two numerical examples are given to illustrate the effectiveness of the proposed design methodology

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

robust h control for discrete time fuzzy systems via basis dependent lyapunov functions this paper deals with the robust h control problem for a class of discrete time fuzzy systems with uncertainty the uncertainty is assumed to be of structured linear fractional form by using basis dependent lyapunov function an h control design approach is developed the control design approach is facilitated by introducing some additional instrumental matrix variables these additional matrix variables decouple the lyapunov and the system matrices which makes the control design feasible the proposed approach leads to some sufficient results in the form of strict linear matrix inequalities lmis it is expected that the basis dependent results are less conservative than the basis independent ones due to the introduction of basis dependent lyapunov function finally numerical examples including the discrete chaotic lorenz system are also given to demonstrate the applicability of the proposed approach

asymptotically necessary and sufficient conditions for stability and performance in fuzzy control applications of polya s theorem stability and performance requirements in fuzzy control of takagi sugeno systems are usually stated as fuzzy summations i e sums of terms related to lyapunov functions which are weighted by membership functions or products of them this paper presents an application to fuzzy control of polya s theorems on positive forms on the standard simplex the result provides a set of progressively less conservative sufficient conditions for proving positivity of fuzzy summations such conditions are less and less conservative as a complexity parameter n increases particular cases of such conditions are those in c h fang y s liu s w kau l hong c h lee a new lmi based approach to relaxed quadratic stabilization of t s fuzzy control systems ieee trans fuzzy systems 14 2006 286 397 x liu q zhang new approaches to h controller designs based on fuzzy observers for t s fuzzy systems via lmi automatica 39 9 2003 1571 1582 with n 2 and 3 respectively the proposed conditions are asymptotically exact i e necessary and sufficient when n tends to infinity or equivalently when a tolerance parameter tends to zero

generating functional analysis of minority games with real market histories it is shown how the generating functional method of de dominicis can be used to solve the dynamics of the original version of the minority game mg in which agents observe real as opposed to fake market histories here one again finds exact closed equations for correlation and response functions but now these are defined in terms of two connected effective non markovian stochastic processes a single effective agent equation similar to that of the fake history models and a second effective equation for the overall market bid itself the latter is absent in fake history models the result is an exact theory from which one can calculate from first principles both the persistent observables in the mg and the distribution of history frequencies

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

mean square admissibility for stochastic ts fuzzy singular systems based on extended quadratic lyapunov function approach the mean square admissibility problem of stochastic ts fuzzy singular systems via an extended quadratic lyapunov function is investigated in this paper comparing with the existing quadratic lyapunov function method the extended quadratic lyapunov function method can relax stabilization conditions firstly the sufficient condition is given for the mean square admissibility of stochastic ts fuzzy singular systems based on an extended quadratic lyapunov function approach secondly two sufficient conditions for mean square admissibility of closed loop systems via the parallel distributed compensation pdc fuzzy controller and non parallel distributed compensation non pdc fuzzy controller are proposed furthermore through the extended quadratic lyapunov function method and non pdc fuzzy controller the less conservative mean square admissibility conditions on solving fuzzy controllers are derived in terms of linear matrix inequalities lmis finally some simulation examples are given to show the effectiveness and merits of the proposed fuzzy controller design methodology

fuzzy weighting dependent approach to h_ infty filter design for time delay fuzzy systems this correspondence is concerned with the hinfin filter design for takagi sugeno t s fuzzy systems with state delay a delay dependent design method is proposed in terms of linear matrix inequalities lmi the main contribution is the use of fuzzy weighting dependent lyapunov functionals which can reduce the conservatism arisen from the quadratic lyapunov functional approach an illustrative example is given to show the effectiveness of the present method

output feedback lmi tracking control conditions with h criterion for uncertain and disturbed t s models this work concerns the tracking problem of uncertain takagi sugeno t s continuous fuzzy model with external disturbances the objective is to get a model reference based output feedback tracking control law the control scheme is based on a pdc structure a fuzzy observer and a h performance to attenuate the external disturbances the stability of the whole closed loop model is investigated using the well known quadratic lyapunov function the key point of the proposed approaches is to achieve conditions under a lmi linear matrix inequalities formulation in the case of an uncertain and disturbed t s fuzzy model this formulation facilitates obtaining solutions through interior point optimization methods for some nonlinear output tracking control problems finally a simulation is provided on the well known inverted pendulum testbed to show the efficiency of the proposed approach

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

distributed non fragile filtering in sensor networks with energy constraints this paper investigates the distributed filtering problem for sensor networks with energy constraint and filter gain variation firstly two strategies are proposed to reduce energy consumption i e the measurement size and the transmission rate reduction strategies to reduce the measurement size a useful measurement selection policy is introduced to choose which element of local measurements is transmitted the selected measurement which has a smaller size than the original one is then stochastically transmitted in order to reflect the imprecision in filter implementation the additive filter gain variation problem is considered based on the switched system approach and some stochastic system analysis methods a sufficient condition is obtained such that the filtering error system is exponentially stable in the mean square sense and a prescribed h performance level is guaranteed filter gains are shown to be determined by solving a set of linear matrix inequalities lmis finally a simulation example is given to demonstrate the effectiveness of the proposed design

dynamics of the eigen and the crow kimura models for molecular evolution we introduce an alternative way to study molecular evolution within well established hamilton jacobi formalism showing that for a broad class of fitness landscapes it is possible to derive dynamics analytically within the 1n accuracy where n is the genome length for a smooth and monotonic fitness function this approach gives two dynamical phases smooth dynamics and discontinuous dynamics the latter phase arises naturally with no explicite singular fitness function counterintuitively the hamilton jacobi method yields straightforward analytical results for the models that utilize fitness as a function of hamming distance from a reference genome sequence we also show the way in which this method gives dynamical phase structure for multipeak fitness

statistical mechanics of the mixed majority minority game with random external information we study the asymptotic macroscopic properties of the mixed majority minority game modelling a population in which two types of heterogeneous adaptive agents namely fundamentalists driven by differentiation and trend followers driven by imitation interact the presence of a fraction f of trend followers is shown to induce a a significant loss of informational efficiency with respect to a pure minority game in particular an efficient unpredictable phase exists only for f 1 2 we solve the model by means of an approximate static replica theory and by a direct dynamical generating functional technique the two approaches coincide and match numerical results convincingly

a delay dependent approach to robust h sub spl infin filtering for uncertain discrete time state delayed systems a delay dependent approach to robust h sub spl infin filtering is proposed for linear discrete time uncertain systems with multiple delays in the state the uncertain parameters are supposed to reside in a polytope and the attention is focused on the design of robust filters guaranteeing a prescribed h sub spl infin noise attenuation level the proposed filter design methodology incorporates some recently appeared results such as moon s new version of the upper bound for the inner product of two vectors and de oliveira s idea of parameter dependent stability which greatly reduce the overdesign introduced in the derivation process in addition to the full order filtering problem the challenging reduced order case is also addressed by using different linearization procedures both full and reduced order 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 numerical examples have been presented to illustrate the feasibility and advantages of the proposed methodologies

robust nonfragile kalman filtering for uncertain linear systems with estimator gain uncertainty the note is concerned with the problem of a robust nonfragile kalman filter design for a class of uncertain linear systems with norm bounded uncertainties the designed state estimator can tolerate multiplicative uncertainties in the state estimator gain matrix the robust nonfragile state estimator designs are given in terms of solutions to algebraic riccati equations the designs guarantee known upper bounds on the steady state error covariance a numerical example is given to illustrate the results

dynamics of a spherical minority game we present an exact dynamical solution of a spherical version of the batch minority game mg with random external information the control parameters in this model are the ratio of the number of possible values for the public information over the number of agents and the radius of the spherical constraint on the microscopic degrees of freedom we find a phase diagram with three phases two without anomalous response an oscillating versus a frozen state and a further frozen phase with divergent integrated response in contrast to standard mg versions we can also calculate the volatility exactly our study reveals similarities between the spherical and the conventional mg but also intriguing differences numerical simulations confirm our analytical results

h 2 and h _ infty filtering design subject to implementation uncertainty this paper presents new filtering design procedures for discrete time linear systems it provides a solution to the problem of linear filtering design assuming that the filter is subject to parametric uncertainty the problem is relevant since the proposed filter design incorporates real world implementation constraints that are always present in practice the transfer function and the state space realization of the filter are simultaneously computed the design procedure can also handle plant parametric uncertainty in this case the plant parameters are assumed not to be exactly known but belonging to a given convex and closed polyhedron robust performance is measured by the h2 and h infty norms of the transfer function from the noisy input to the filtering error the results are based on the determination of an upper bound on the performance objectives all optimization problems are linear with constraint sets given in the form of lmi linear matrix inequalities global optimal solutions to these problems can be readily computed numerical examples illustrate the theory

relaxed stabilization conditions for continuous time takagi sugeno fuzzy control systems this paper deals with the stabilization of continuous time takagi sugeno t s fuzzy control systems based on fuzzy lyapunov functions and nonparallel distributed compensation non pdc control laws new stabilization conditions are represented in the form of linear matrix inequalities lmis the theoretical proof shows that the proposed conditions can provide less conservatism than the existing results in the literature moreover in order to demonstrate the effectiveness of the non pdc control laws the problem of h controller design for t s fuzzy systems is also studied simulation examples are given to illustrate the merits of the proposed methods

generating functional analysis of minority games with inner product strategy definitions we use generating functional methods to solve the so called inner product versions of the minority game mg with fake and or real market histories by generalizing the theory developed recently for look up table mgs with real histories the phase diagrams of the look up table and inner product mg versions are generally found to be identical with the exception of inner product mgs where histories are sampled linearly which are found to be structurally critical however we encounter interesting differences both in the theory where the role of the history frequency distribution in look up table mgs is taken over by the eigenvalue spectrum of a history covariance matrix in inner product mgs and in the static and dynamic phenomenology of the models our theoretical predictions are supported by numerical simulations

a descriptor system approach to fuzzy control system design via fuzzy lyapunov functions there has been a flurry of research activities in the analysis and design of fuzzy control systems based on linear matrix inequalities lmis this paper presents a descriptor system approach to fuzzy control system design using fuzzy lyapunov functions the design conditions are still cast in terms of lmis but the proposed approach takes advantage of the redundancy of descriptor systems to reduce the number of lmi conditions which leads to less computational requirement to obtain relaxed lmi conditions new types of fuzzy controller and fuzzy lyapunov function are proposed a salient feature of the lmi conditions derived in this paper is to relate the feasibility of the lmis to the switching speed of each linear subsystem to be exact to the lower bounds of time derivatives of membership functions to illustrate the validity and applicability of the proposed approach two design examples are provided the first example shows that the lmi conditions based on the fuzzy lyapunov function are less conservative than those based on a common standard lyapunov function the second example illustrates the utility of the fuzzy lyapunov function approach in comparison with a piecewise lyapunov function approach

a new design of delay dependent robust cal h _ bm infty filtering for discrete time t s fuzzy systems with time varying delay this paper investigates the problem of delay dependent robust h infin filtering design for a class of uncertain discrete time state delayed takagi sugeno t s fuzzy systems the state delay is assumed to be time varying and of an interval like type which means that both the lower and upper bounds of the time varying delay are available the parameter uncertainties are assumed to have a structured linear fractional form based on a novel fuzzy basis dependent lyapunov krasovskii functional combined with finsler s lemma and an improved free weighting matrix technique for delay dependent criteria a new sufficient condition for robust h infin performance analysis is first derived and then the filter synthesis is developed it is shown that by using a simple linearization technique incorporating a bounding inequality a unified framework can be developed such that both the full order and reduced order filters can be obtained by solving a set of linear matrix inequalities lmis which are numerically efficient with commercially available software finally simulation examples are provided to illustrate the advantages and less conservatism of the proposed approach

lmi based relaxed nonquadratic stabilization conditions for nonlinear systems in the takagi sugeno s form this paper presents the stabilization analysis for a class of nonlinear systems that are represented by a takagi and sugeno ts discrete fuzzy model takagi and sugeno ieee trans systems man cybern 15 1 1985 116 the main result given here concerns their stabilization using new control laws and new nonquadratic lyapunov functions new relaxed conditions and linear matrix inequality based design are proposed that allow outperforming previous results found in the literature two examples are also provided to demonstrate the efficiency of the approaches

nonfragile quantized h filtering for discrete time switched t s fuzzy systems with local nonlinear models this paper addresses the h infty filtering problem for a class of discrete time nonlinear switched systems every subsystem of the considered nonlinear switched systems is represented by the takagi sugeno t s fuzzy systems with local nonlinear models signal quantization and filter parameter perturbation are considered simultaneously in the h infty filter design both the measurement output signal and the performance output signal are quantized by two static quantizers respectively before they are transmitted based on the average dwell time approach sufficient conditions for desired h infty filters are established in the form of linear matrix inequalities lmis under the obtained conditions the filtering error system is exponentially stable and can achieve a weighted h infty performance index finally a numerical example and a practical example are provided to illustrate the effectiveness of the obtained results

generating functional analysis of batch minority games with arbitrary strategy numbers both the phenomenology and the theory of minority games mg with more than two strategies per agent are different from those of the conventional and extensively studied case s 2 mgs with s 2 exhibit nontrivial statistics of the frequencies with which the agents select from their available decision making strategies with far reaching implications in the few theoretical mg studies with s 2 published so far these statistics could not be calculated analytically this prevented solution even in ergodic stationary states equations for order parameters could only be closed approximately using simulation data here we carry out a generating functional analysis of fake history batch mgs with arbitrary values of s and give an analytical solution of the strategy frequency problem this leads to closed equations for order parameters in the ergodic regime exact expressions for strategy selection statistics and phase diagrams our results find perfect confirmation in numerical simulations

a new method for the solution of models of biological evolution derivation of exact steady state distributions we investigate well known models of biological evolution and address the open problem of how construct a correct continuous analog of mutations in discrete sequence space we deal with models where the fitness is a function of a hamming distance from the reference sequence the mutation selection master equation in the discrete sequence space is replaced by a hamilton jacobi equation for the logarithm of relative frequencies of different sequences the steady state distribution mean fitness and the variance of fitness are derived all our results are asymptotic in the large genome limit a variety of important biological and biochemical models can be solved by this new approach

decentralized h_ infty filter design for discrete time interconnected fuzzy systems this paper describes a decentralized h infin filter design for discrete time interconnected fuzzy systems based on piecewise quadratic lyapunov functions the systems consist of j discrete time interconnected takagi sugeno t s fuzzy subsystems and a decentralized h infin filter is designed for each subsystem it is shown that the stability of the overall filtering error system with h infin performance can be established if a piecewise quadratic lyapunov function can be constructed moreover the parameters of filters can be obtained by solving a set of linear matrix inequalities that are numerically feasible two simulation examples are given to show the effectiveness of the proposed approach