stability analysis and synthesis of nonlinear time delay systems via linear takagi sugeno fuzzy models abstract this paper concerns with the stability analysis and synthesis of nonlinear retarded systems via linear takagi sugeno ts fuzzy model approach first the ts fuzzy models with time delay are present and the stability conditions are derived using lyapunov razumikhin functional approach then a stabilization approach for nonlinear retarded systems through fuzzy state feedback and fuzzy observer based controller is proposed it shows that the analysis results provide an efficient technique for the design of fuzzy controllers sufficient conditions for the existence of fuzzy state feedback gain and fuzzy observer gain of the time delay systems are derived through the numerical solution of a set of coupled linear matrix inequalities

technical communique sliding mode control with bounded l 2 gain performance of markovian jump singular time delay systems in this paper we investigate the problem of sliding mode control smc of markovian jump singular time delay systems the aim is to consider the bounded 2 gain performance in the analysis of sliding mode dynamics thus to improve the transient performance of the smc system firstly a delay dependent bounded real lemma is proposed for the underlying system to be stochastically admissible while achieving the prescribed bounded 2 gain performance condition an integral type switching surface function is designed by taking the singular matrix into account thus the resulting sliding mode dynamics is a full order singular markovian jump time delay system then the sliding mode dynamics is analyzed and the solvability condition for the desired switching surface function is derived moreover an smc law is synthesized to drive the system trajectories onto the predefined switching surface in a finite time finally a numerical example is provided to illustrate the effectiveness of the proposed techniques

robust stabilization for uncertain markovian jump fuzzy systems based on free weighting matrix method this paper presents a new methodology of robust state feedback fuzzy controller based on free weighting matrix method for a class of uncertain markovian jump nonlinear systems the class of systems under consideration is represented by the t s fuzzy model with partly known transition probability matrix the free weighting matrix method is proposed to obtain a less conservative stochastic stability criterion of the uncertain markovian jump fuzzy systems mjfss in terms of linear matrix inequalities lmis furthermore a sufficient condition for the mode dependent state feedback fuzzy controller is derived for the mjfss for all admissible parameter uncertainties finally a simulation example is provided to illustrate the effectiveness of the proposed methodology

reliable mixed h passive control for t s fuzzy delayed systems based on a semi markov jump model approach abstract this paper investigates the problem of the reliable mixed h passive control for takagi sugeno t s fuzzy delayed systems based on a semi markov jump model smjm approach the focus is to design a fuzzy fault tolerant controller such that the resulting closed loop system is stochastically stable with a prescribed mixed h passive performance level even if the actuator failures appear a semi markov process is employed to describe the encountered failures of the actuator by applying the lyapunov krasovskii method in combination with some novel inequalities some conditions on the performance analysis are established where some negative quadratic terms are fully considered to reduce the conservatism based on the conditions an explicit expression for the desired controller is given three numerical examples are presented to show the effectiveness and reduced conservatism of the proposed method

finite time h control for t s fuzzy descriptor semi markov jump systems via static output feedback abstract this paper is concerned with the finite time static output feedback h controller design problem for a type of nonlinear continuous time descriptor semi markov jump systems s mjss via takagi sugeno t s fuzzy model where the transition rates are time varying and dependent on sojourn time firstly based on the stochastic lyapunov functional sufficient conditions on singular stochastic h finite time boundedness ss h ftb for continuous time t s fuzzy descriptor s mjss are given then in order to design the static output feedback controller easily the closed loop system is represented in an augmented form furthermore based on the lower and upper bounds of the time varying transition rates and by using the matrix inequality decoupling technique a novel linear matrix inequality lmi condition on ss h ftb of closed loop system is presented meanwhile the static output feedback controller is developed in terms of lmis the proposed design method doesn t impose any constraints on system matrices or slack variables which shows less conservative results lastly numerical examples are given to demonstrate the effectiveness of the obtained methods

new passivity analysis for neural networks with discrete and distributed delays in this brief the problem of passivity analysis is investigated for a class of uncertain neural networks nns with both discrete and distributed time varying delays by constructing a novel lyapunov functional and utilizing some advanced techniques new delay dependent passivity criteria are established to guarantee the passivity performance of nns essentially different from the available results when estimating the upper bound of the derivative of lyapunov functionals we consider and best utilize the additional useful terms about the distributed delays which leads to less conservative results these criteria are expressed in the form of convex optimization problems which can be efficiently solved via standard numerical software numerical examples are provided to illustrate the effectiveness and less conservatism of the proposed results

bethe ansatz results for hubbard chains with toroidal boundary conditions we solve exactly the problem of a one dimensional repulsive u hubbard chain with toroidal boundary conditions htb using the bethe ansatz approach we calculate analytically the finite size corrections to the ground state energy in the half filled case and use this expression to derive charge and spin stiffnesses with no assumptions we then use a particle hole transformation to calculate the finite size corrections for the half filledattractive u case and again derive the resulting expressions for the charge and spin stiffnesses lastly we discuss how the repulsive u corrections relate to those of a heisenberg model with toroidal boundary conditions

time quantization and q deformations we extend to quantum mechanics the technique of stochastic subordination by means of which one can express any semi martingale as a time changed brownian motion as examples we considered two versions of the q deformed harmonic oscillator in both ordinary and imaginary time and show how these various cases can be understood as different patterns of time quantization rules

filtering based robust fault detection of fuzzy jump systems this paper studies the robust fault detection filter rfdf design problems for uncertain nonlinear markov jump systems with state delays and parameter uncertainties by means of takagi sugeno fuzzy models the dynamics of filtering error generator and the fuzzy rfdf system are constructed with the aid of the selected weighting matrix function the design objective is to find an optimal rfdf which results in a minimal difference between the reference model ideal solution and the rfdf real solution to be designed a sufficient condition is firstly established on the stochastic stability by using stochastic lyapunov krasovskii functional approach then in terms of linear matrix inequalities techniques sufficient conditions on the existence of fuzzy rfdf are presented and proved finally the design problem is formulated as an optimization algorithm simulation results illustrate that the proposed rfdf can detect the faults shortly after the occurrences

improved fuzzy control design for nonlinear markovian jump systems with incomplete transition descriptions this paper addresses the state feedback control of nonlinear continuous time markovian jump systems the nonlinearity is represented by takagi sugeno fuzzy models and the transition probability matrix is assumed to be partly known some elements in the matrix are known some are unknown but with known lower and upper bounds and some are completely unknown by making full use of the continuous property of the transition probability matrix new sufficient conditions for the stochastic stability of the system are obtained in terms of linear matrix inequalities we show that the conditions given are less conservative than or at least the same as those for existing results moreover using the conditions obtained we establish a method for design of a h state feedback controller numerical examples illustrate the effectiveness of the proposed method

technical communique dissipative analysis and control of state space symmetric systems the paper addresses the problem of analysis and static output feedback control synthesis for strict quadratic dissipativity of linear time invariant systems with state space symmetry as a particular case of dissipative systems we consider the mixed h and positive real performance criterion and we develop an explicit expression for calculating the h norm of these systems subsequently an explicit parametrization of the static output feedback control gains that solve the mixed h and positive real performance problem is obtained numerical examples demonstrate the use and computational advantages of the proposed explicit solutions

adaptive fuzzy backstepping control for a class of nonlinear systems with sampled and delayed measurements this paper investigates the adaptive fuzzy backstepping control and h infty performance analysis for a class of nonlinear systems with sampled and delayed measurements in the control scheme a fuzzy estimator fe model is used to estimate the states of the controlled plant while the fuzzy logic systems are used to approximate the unknown nonlinear functions in the nonlinear system the controller is obtained based on the fe model by combining the backstepping technique with the classic adaptive fuzzy control method in the stability analysis all the signals in the closed loop system are guaranteed to be semiglobally uniformly ultimately bounded suub and the outputs of the system are proven to converge to a small neighborhood of origin furthermore the h infty performance is investigated and the outputs of the closed loop system are bounded in the h infty sense two examples are given to illustrate the effectiveness of the proposed control scheme

fuzzy semi markov migration process in credit risk we explore the rating system used by credit agencies with a focus on problems that justify the use of fuzzy set theory we prove that a fuzzy market is viable if and only if an equivalent martingale measure exists from which we construct the forward probability measure and under which the discounted price of a default free bond is a martingale we model the evolution of credit migration of a defaultable bond as an inhomogeneous semi markov process with fuzzy states we study the effects of changing the real probability measure to a forward probability measure in addition we investigate the asymptotic behaviour of the survival probability in each fuzzy state given in the absence of default finally we discuss parameter estimation and calibration of the inhomogeneous markov chain with fuzzy states

fault estimation and tolerant control for fuzzy stochastic systems this paper deals with the problem of fault estimation and fault tolerant control for takagi sugeno t s fuzzy stochastic systems with sensor failures where the system under consideration contains ito type stochastic disturbances a new robust observer technique is presented to obtain the estimates of the system states and the sensor faults simultaneously and a fuzzy fault tolerant control scheme is developed to guarantee the closed loop system to be exponentially stable in mean square sufficient conditions are obtained for the existence of admissible controllers and it is shown that the reachability of the sliding mode dynamics can be guaranteed under the proposed control techniques finally a numerical example is provided to illustrate the effectiveness and applicability of the theoretic results obtained

static output feedback h control of a class of nonlinear discrete time systems this paper is concerned with the problem of designing robust h static output feedback sof controllers for a class of discrete time nonlinear systems which are represented by t s fuzzy models by considering the properties of system output matrices a method for h sof control synthesis is developed in terms of solutions to a set of linear matrix inequalities lmis in contrast to the existing techniques for designing sof controllers the new proposed method can give less conservative results by removing the constraint that the considered lyapunov matrix is diagonal numerical examples are given to illustrate the effectiveness of the proposed design method

improved delay dependent robust stabilization conditions of uncertain t s fuzzy systems with time varying delay this paper aims to develop simplified yet improved delay dependent robust control for uncertain t s fuzzy systems with time varying delay this is achieved through constructing new lyapunov krasovskii functionals and improving jensen s inequality unlike existing work in this area the approach developed in this paper employs neither free weighing matrices nor model transformations as a result simplified yet improved stability conditions are obtained for t s fuzzy systems with norm bounded type uncertainties for controller synthesis of the fuzzy systems the stabilization problem with memoryless state feedback control is solved via utilizing a cone complementarity minimization algorithm numerical examples are given to demonstrate the effectiveness of the proposed approach

extended dissipative state estimation for markov jump neural networks with unreliable links this paper is concerned with the problem of extended dissipativity based state estimation for discrete time markov jump neural networks nns where the variation of the piecewise time varying transition probabilities of markov chain is subject to a set of switching signals satisfying an average dwell time property the communication links between the nns and the estimator are assumed to be imperfect where the phenomena of signal quantization and data packet dropouts occur simultaneously the aim of this paper is to contribute with a markov switching estimator design method which ensures that the resulting error system is extended stochastically dissipative in the simultaneous presences of packet dropouts and signal quantization stemmed from unreliable communication links sufficient conditions for the solvability of such a problem are established based on the derived conditions an explicit expression of the desired markov switching estimator is presented finally two illustrated examples are given to show the effectiveness of the proposed design method

robust extended dissipative control for sampled data markov jump systems this paper investigates the problem of the sampled data extended dissipative control for uncertain markov jump systems the systems considered are transformed into markov jump systems with polytopic uncertainties and sawtooth delays by using an input delay approach the focus is on the design of a mode independent sampled data controller such that the resulting closed loop system is mean square exponentially stable with a given decay rate and extended dissipative a novel exponential stability criterion and an extended dissipativty condition are established by proposing a new integral inequality the reduced conservatism of the criteria is demonstrated by two numerical examples furthermore a sufficient condition for the existence of a desired mode independent sampled data controller is obtained by solving a convex optimisation problem finally a resistance inductance and capacitance rlc series circuit is employed to illustrate the effectiveness of the proposed approach

feedback and optimal sensitivity model reference transformations multiplicative seminorms and approximate inverses in this paper the problem of sensitivity reduction by feedback is formulated as an optimization problem and separated from the problem of stabilization stable feedback schemes obtainable from a given plant are parameterized salient properties of sensitivity reducing schemes are derived and it is shown that plant uncertainty reduces the ability of feedback to reduce sensitivity the theory is developed for input output systems in a general setting of banach algebras and then specialized to a class of multivariable time invariant systems characterized by n times n matrices of h infty frequency response functions either with or without zeros in the right half plane the approach is based on the use of a weighted seminorm on the algebra of operators to measure sensitivity and on the concept of an approximate inverse approximate invertibility of the plant is shown to be a necessary and sufficient condition for sensitivity reduction an indicator of approximate invertibility called a measure of singularity is introduced the measure of singularity of a linear time invariant plant is shown to be determined by the location of its right half plane zeros in the absence of plant uncertainty the sensitivity to output disturbances can be reduced to an optimal value approaching the singularity measure in particular if there are no right half plane zeros sensitivity can be made arbitrarily small the feedback schemes used in the optimization of sensitivity resemble the lead lag networks of classical control design some of their properties and methods of constructing them in special cases are presented

a novel approach to stability and stabilization of fuzzy sampled data markovian chaotic systems abstract this paper studies the problems of stability and stabilization of a class of markovian chaotic systems via fuzzy sampled data control different from some existing results the markovian jumping with general uncertain transition rates is considered for such systems a novel approach i e input delay dependent vector approach is proposed for the first time based on this approach an input delay dependent lyapunov krasovskii functional lkf with cubic function of input delay is successfully constructed and the convex combination technique is used with ease to derive stability and stabilization criteria compared with some existing stability and stabilization criteria for chaotic systems our results are not only less conservative but also with reduced calculation complexity finally the superiorities of proposed results are illustrated by two numerical examples

parameterized linear matrix inequality techniques in fuzzy control system design this paper proposes different parameterized linear matrix inequality plmi characterizations for fuzzy control systems these plmi characterizations are in turn relaxed into pure lmi programs which provides tractable and effective techniques for the design of suboptimal fuzzy control systems the advantages of the proposed methods over earlier ones are then discussed and illustrated through numerical examples and simulations

robust h fuzzy control for uncertain nonlinear markovian jump systems with time varying delay this paper investigates the problem of robust h fuzzy control for a class of uncertain nonlinear markovian jump systems with time varying delay the class of systems under consideration is described by the takagi sugeno fuzzy model the goal of the paper is to design a mode dependent fuzzy state feedback controller such that the closed loop system is stochastically stable with a prescribed h performance of disturbance attenuation for all admissible parameter uncertainties in order to obtain a less conservative control design a new stochastic lyapunov krasovskii functional is first constructed by decomposing the delay interval into multiple equidistant subintervals then by employing this functional a delay decomposition approach to the design of robust h fuzzy controllers is developed in terms of linear matrix inequalities finally two examples are given to illustrate the merit and usability of the proposed design method

passivity analysis and passive control of fuzzy systems with time varying delays this paper is concerned with the passive controller design problem for a class of continuous time takagi sugeno t s fuzzy systems with both state and input delays the delays are assumed to be time varying and differentiable a notion of very strict passivity is adopted the purpose is to design a state feedback fuzzy controller such that the resulting closed loop system is very strictly passive vsp delay dependent conditions for the solvability of the addressed problem are obtained by applying recently developed techniques for time delay systems and fuzzy systems these conditions are expressed by means of strict linear matrix inequalities lmis that can be easily solved a numerical example and simulation results are provided to demonstrate the effectiveness of the proposed method

local stabilization for discrete time t s fuzzy time delay systems with sensor fault abstract this paper focuses on a local stabilization problem for discrete time t s fuzzy time delay systems with sensor fault and external disturbances the main purpose is to synthesize a controller such that the state can be restricted into a pre specified region even when the system is subject to sensor fault and external disturbance first by restricting the reachable set into an ellipsoid set which is contained in the objective domain the system state is restricted into the objective area such that the local stabilization can be achieved second the differential mean value theorem is used to determine the bound of the deviation between the membership function of the system and that of the controller then the information of the deviation is employed for designing the controller different from some existing methods in the proposed method the influence of the sensor fault on the membership function of the controller has been fully considered and the information of aforementioned deviation is made full use of such that a less conservative stability criterion can be derived meanwhile due to the use of the differential mean value theorem the deviation bound can be calculated then the requirement where the deviation bound of is assumed to be previously known is removed finally an example is presented to verify the effectiveness of the proposed method

conditions of output stabilization for nonlinear models in the takagi sugeno s form this paper deals with the control law design with an observer for models in the takagi sugeno s ts form in the general case where the nonlinearities and the variables involved are not measurable the results presented in this paper give sufficient conditions of stabilization for the global loop i e ts model stabilized with a state feedback and a fuzzy observer conditions are given in the form of linear matrix inequalities lmi problem

infinite horizon h control for nonlinear stochastic markov jump systems with x u v dependent noise via fuzzy approach in this paper the h control problem is studied for nonlinear stochastic markov jump systems with state control and external disturbance dependent noise x u v dependent noise for short a sufficient condition is derived for the infinite horizon h control of such systems in terms of a set of coupled second order hamilton jacobi inequalities hjis in general it is difficult to solve these coupled hjis by using fuzzy approach the infinite horizon h control design for nonlinear stochastic markov jump systems is developed via solving a set of linear matrix inequalities lmis instead of hjis two numerical examples are presented to illustrate the effectiveness of the proposed design methods

observer design for takagi sugeno descriptor models this paper considers observer design for nonlinear descriptor systems we propose approaches based on takagi sugeno ts models an extended estimation vector is used in order to keep the descriptor structure of the observer the design conditions are expressed as linear matrix inequalities the proposed observer structure via an intermediate variable as estimated variable is able to recover the previous observer results for ts descriptors moreover through a direct extension via so called finsler s lemma relaxed conditions are obtained numerical examples show the effectiveness of the proposed approaches

stability and dissipativity analysis of distributed delay cellular neural networks in this brief the problems of delay dependent stability analysis and strict q s dissipativity analysis are investigated for cellular neural networks cnns with distributed delay first by introducing an integral partitioning technique two new forms of lyapunov krasovskii functionals are constructed and improved distributed delay dependent stability conditions are established in terms of linear matrix inequalities based on this criterion a new sufficient delay and dependent condition is given to guarantee that the cnns with distributed delay are strictly q s dissipative the results developed in this brief can tolerate larger allowable delay than existing ones in the literature which is demonstrated by several examples

reliable h_ infty control for discrete time fuzzy systems with infinite distributed delay in this paper the problem of reliable h control is investigated for discrete time takagi sugeno t s fuzzy systems with infinite distributed delay and actuator faults a discrete time homogeneous markov chain is used to represent the stochastic behavior of actuator faults in terms of a stochastic fuzzy lyapunov functional a sufficient condition is proposed to ensure that the resultant closed loop system is exponentially stable in the mean square sense with an h performance index based on the derived condition the reliable h control problem is solved and an explicit expression of the desired controller is also given the case of no failure in the actuator is also considered a numerical example is given to demonstrate that our results are effective and less conservative

fault detection for discrete time markov jump linear systems with partially known transition probabilities in this article the fault detection fd problem for a class of discrete time markov jump linear system mjls with partially known transition probabilities is investigated the proposed systems are more general which relax the traditional assumption in markov jump systems that all the transition probabilities must be completely known a residual generator is constructed and the corresponding fd is formulated as an h filtering problem by which the error between residual and fault are minimised in the h sense the linear matrix inequality based sufficient conditions for the existence of fd filter are derived a numerical example on a multiplier accelerator model economic system is given to illustrate the potential of the developed theoretical results

robust consensus control for a class of multi agent systems via distributed pid algorithm and weighted edge dynamics abstract this paper studies the robust proportional integral derivative pid consensus control for a class of linear multi agent systems mass with external disturbances different from the existing results both the consensus analysis and the transient performance characteristics for high order linear mass are considered based on a factorization of laplacian matrix the initial mas is firstly transformed into the so called weighted edge dynamics and then a design equivalence between the proposed pid consensus controller and the corresponding stabilizing controller for such weighted edge dynamics is presented via some graph theory results furthermore by combining lyapunov theory and barbalat s lemma it is proved that both the stabilization of weighted edge dynamics and the consensus of mas can be guaranteed even in the presence of external disturbances in particular some relationships between the transient time performance of weighted edge dynamics and the pid design parameters are given finally some numerical examples on lc oscillator network are provided to illustrate the validity of theoretical results

mixed h infinity and passive filtering for discrete fuzzy neural networks with stochastic jumps and time delays in this brief the problems of the mixed h infinity and passivity performance analysis and design are investigated for discrete time delay neural networks with markovian jump parameters represented by takagi sugeno fuzzy model the main purpose of this brief is to design a filter to guarantee that the augmented markovian jump fuzzy neural networks are stable in mean square sense and satisfy a prescribed passivity performance index by employing the lyapunov method and the stochastic analysis technique applying the matrix decomposition techniques sufficient conditions are provided for the solvability of the problems which can be formulated in terms of linear matrix inequalities a numerical example is also presented to illustrate the effectiveness of the proposed techniques