approaches to t s fuzzy affine model based reliable output feedback control for nonlinear ito stochastic systems this paper deals with the problem of reliable and robust mathscr h infty static output feedback sof controller synthesis for continuous time nonlinear stochastic systems with actuator faults the nonlinear stochastic plant is expressed by an ito type takagi sugeno fuzzy affine model with parametric uncertainties and a markov process is employed to model the occurrence of actuator fault the purpose is to design an admissible piecewise sof controller such that the resulting closed loop system is stochastically stable with a prescribed disturbance attenuation level in an mathscr h infty sense specifically based on a markovian lyapunov function combined with ito differential formula s procedure and some matrix inequality convexification procedures two new approaches to the reliable sof controller analysis and synthesis are proposed for the underlying stochastic fuzzy affine systems it is shown that the existence of desired reliable controllers is fully characterized in terms of strict linear matrix inequalities finally simulation examples are presented to illustrate the effectiveness and advantages of the developed methods

bounds on colength and maximal multiplicity sequences let a be a characteristic zero p i algebra with cocharacters n a m we obtain upper and lower bounds on max n m and n m and compute the exact rates of growth when a is a prime product algebra

fault estimation observer design for discrete time takagi sugeno fuzzy systems based on piecewise lyapunov functions this paper studies the problem of robust fault estimation fe observer design for discrete time takagi sugeno t s fuzzy systems via piecewise lyapunov functions both the full order fe observer ffeo and the reduced order fe observer rfeo are presented the objective of this paper is to establish a novel framework of the fe observer with less conservatism first under the multiconstrained design an ffeo is proposed to achieve fe for discrete time t s fuzzy models then using a specific coordinate transformation an rfeo is constructed which results in a new fault estimator to realize fe using current output information furthermore by the piecewise lyapunov function approach less conservative results on both ffeo and rfeo are derived by introducing slack variables simulation results are presented to illustrate the advantages of the theoretic results that are obtained in this paper

robust h control of uncertain fuzzy systems under time varying sampling robust h sampled data control for uncertain fuzzy systems is discussed in many practical situations a system is modeled as a continuous time fuzzy system while the control input is the zero order hold which can be represented as a piecewise continuous delay here we take a delay system approach to the h sampled data control problem the closed loop system with a sampled data state feedback controller becomes a system with time varying delay first h performance conditions for the closed loop system are given in terms of linear matrix inequalities lmis such conditions are derived by using the leibniz newton formula and free weighting matrix method for fuzzy time delay systems under the assumption that sampling time is not greater than some prescribed number then a design method for a robust h sampled data state feedback controller for uncertain fuzzy systems is proposed numerical examples are given to illustrate our robust h sampled data state feedback control design

model approximation for discrete time state delay systems in the t s fuzzy framework this paper is concerned with the problem of h model approximation for discrete time takagi sugeno t s fuzzy time delay systems for a given stable t s fuzzy system our attention is focused on the construction of a reduced order model which not only approximates the original system well in an h performance but is also translated into a linear lower dimensional system by applying the delay partitioning approach a delay dependent sufficient condition is proposed for the asymptotic stability with an h error performance for the error system then the h model approximation problem is solved by using the projection approach which casts the model approximation into a sequential minimization problem subject to linear matrix inequality lmi constraints by employing the cone complementary linearization algorithm moreover by further extending the results h model approximation with special structures is obtained i e delay free model and zero order model finally two numerical examples are provided to illustrate the effectiveness of the proposed methods

an improved input delay approach to stabilization of fuzzy systems under variable sampling in this paper we investigate the problem of stabilization for sampled data fuzzy systems under variable sampling a novel lyapunov krasovskii functional lkf is defined to capture the characteristic of sampled data systems and an improved input delay approach is proposed by the use of an appropriate enlargement scheme new stability and stabilization criteria are obtained in terms of linear matrix inequalities lmis compared with the existing results the newly obtained ones contain less conservatism some illustrative examples are given to show the effectiveness of the proposed method and the significant improvement on the existing results

new approach to delay dependent stability analysis and stabilization for continuous time fuzzy systems with time varying delay this paper is concerned with delay dependent stability analysis and stabilization problems for continuous time takagi and sugeno t s fuzzy systems with a time varying delay a new method for the delay dependent stability analysis and stabilization is suggested which is less conservative than other existing ones first based on a fuzzy lyapunov krasovskii functional lkf a delay dependent stability criterion is derived for the open loop fuzzy systems in the derivation process some free fuzzy weighting matrices are introduced to express the relationships among the terms of the system equation and among the terms in the leibniz newton formula then a delay dependent stabilization condition based on the so called parallel distributed compensation pdc scheme is worked out for the closed loop fuzzy systems the proposed stability criterion and stabilization condition are represented in terms of linear matrix inequalities lmis and compared with the existing ones via two examples finally application to control of a truck trailer is also given to illustrate the effectiveness of the proposed design method

new results on h_ infty tracking control based on the t s fuzzy model for sampled data networked control system this study deals with the problem of h infty tracking control for a sampled data networked control system based on a takagi sugeno fuzzy model an error model is established by combining the input delay and parallel distributed compensation techniques so as to transform the sampling period of a sampler a signal transmission delay and data packet dropouts to the refreshing interval of a zero order hold the method introduces a new augmented lyapunov krasovskii functional to derive a sufficient condition to ensure a prescribed h infty tracking performance with less conservativeness than others a fuzzy controller can easily be designed using the condition a numerical example demonstrates the validity of the method

stability analysis for continuous systems with two additive time varying delay components this paper presents a new result of stability analysis for continuous systems with two additive time varying delay components which represent a general class of delay systems with strong application background in network based control systems this criterion is expressed as a set of linear matrix inequalities which can be readily tested by using standard numerical software a numerical example is provided to show the effectiveness and advantage of the proposed stability condition

a moving bump in a continuous manifold a comprehensive study of the tracking dynamics of continuous attractor neural networks understanding how the dynamics of a neural network is shaped by the network structure and consequently how the network structure facilitates the functions implemented by the neural system is at the core of using mathematical models to elucidate brain functions this study investigates the tracking dynamics of continuous attractor neural networks canns due to the translational invariance of neuronal recurrent interactions canns can hold a continuous family of stationary states they form a continuous manifold in which the neural system is neutrally stable we systematically explore how this property facilitates the tracking performance of a cann which is believed to have clear correspondence with brain functions by using the wave functions of the quantum harmonic oscillator as the basis we demonstrate how the dynamics of a cann is decomposed into different motion modes corresponding to distortions in the amplitude position width or skewness of the network state we then develop a perturbation approach that utilizes the dominating movement of the network s stationary states in the state space this method allows us to approximate the network dynamics up to an arbitrary accuracy depending on the order of perturbation used we quantify the distortions of a gaussian bump during tracking and study their effects on tracking performance results are obtained on the maximum speed for a moving stimulus to be trackable and the reaction time for the network to catch up with an abrupt change in the stimulus

h control for sampled data nonlinear systems described by takagi sugeno fuzzy systems in this paper we consider the design problem of output feedback h controllers for sampled data fuzzy systems we first transfer them into equivalent jump fuzzy systems we establish the so called bounded real lemma for jump fuzzy systems and give a design method of suboptimal output feedback h controllers in terms of two riccati inequalities with jumps we then apply the main results to the sampled data fuzzy systems and obtain a design method of suboptimal output feedback h controllers we give a numerical example and construct a suboptimal output feedback h controller

asynchronous output feedback control of networked nonlinear systems with multiple packet dropouts t s fuzzy affine model based approach this paper investigates the problem of robust output feedback control for a class of networked nonlinear systems with multiple packet dropouts the nonlinear plant is represented by takagi sugeno t s fuzzy affine dynamic models with norm bounded uncertainties and stochastic variables that satisfy the bernoulli random binary distribution are adopted to characterize the data missing phenomenon the objective is to design an admissible output feedback controller that guarantees the stochastic stability of the resulting closed loop system with a prescribed disturbance attenuation level it is assumed that the plant premise variables which are often the state variables or their functions are not measurable so that the controller implementation with state space partition may not be synchronous with the state trajectories of the plant based on a piecewise quadratic lyapunov function combined with an s procedure and some matrix inequality convexifying techniques two different approaches to robust output feedback controller design are developed for the underlying t s fuzzy affine systems with unreliable communication links the solutions to the problem are formulated in the form of linear matrix inequalities lmis finally simulation examples are provided to illustrate the effectiveness of the proposed approaches

brief paper robust sampled data h control with stochastic sampling in this paper the problem of robust h control is investigated for sampled data systems with probabilistic sampling the parameter uncertainties are time varying norm bounded and appear in both the state and input matrices for the simplicity of technical development only two different sampling periods are considered whose occurrence probabilities are given constants and satisfy bernoulli distribution which can be further extended to the case with multiple stochastic sampling periods by applying an input delay approach the probabilistic sampling system is transformed into a continuous time delay system with stochastic parameters in the system matrices by linear matrix inequality lmi approach sufficient conditions are obtained which guarantee the robust mean square exponential stability of the system with an h performance moreover an h controller design procedure is then proposed an illustrative example is included to demonstrate the effectiveness of the proposed techniques

network based h control for singular systems with event triggered sampling scheme in this paper the problem of event triggered h control is investigated for networked singular systems to make full use of the characteristics of networked control system a discrete event triggered communication scheme which only needs to supervise the system state in discrete instants is proposed the sampling interval is employed to unify the networked singular system and the event triggered condition into a new time delay system based on this model sufficient criteria are derived to guarantee the networked singular system regular impulse free and stable with an h norm bound the corresponding state feedback controller is designed a practical example is given to show that the proposed event triggered scheme is more effective and useful than some existing works

spatially piecewise fuzzy control design for sampled data exponential stabilization of semilinear parabolic pde systems this paper employs a takagi sugeno t s fuzzy partial differential equation pde model to solve the problem of sampled data exponential stabilization in the sense of spatial l infty norm vert cdot vert infty for a class of nonlinear parabolic distributed parameter systems dpss where only a few actuators and sensors are discretely distributed in space initially a t s fuzzy pde model is assumed to be derived by the sector nonlinearity method to accurately describe complex spatiotemporal dynamics of the nonlinear dpss subsequently a static sampled data fuzzy local state feedback controller is constructed based on the t s fuzzy pde model by constructing an appropriate lyapunov krasovskii functional candidate and employing vector valued wirtinger s inequalities a variation of vector valued poincare wirtinger inequality in one dimensional spatial domain as well as a vector valued agmon s inequality it is shown that the suggested sampled data fuzzy controller exponentially stabilizes the nonlinear dpss in the sense of vert cdot vert infty if sufficient conditions presented in term of standard linear matrix inequalities lmis are fulfilled moreover an lmi relaxation technique is utilized to enhance exponential stabilization ability of the suggested sampled data fuzzy controller finally the satisfactory and better performance of the suggested sampled data fuzzy controller are demonstrated by numerical simulation results of two examples

robust h sub spl infin control for fuzzy systems with frobenius norm bounded uncertainties in this paper we investigate the problem of robust h sub spl infin performance and stabilization for a class of uncertain fuzzy systems with frobenius norm bounded parameter uncertainties in all system matrices both continuous and discrete time uncertain fuzzy systems are considered under a unified treatment called bounded real lemma for fuzzy systems unlike the bounded real lemma in the linear theory of robust h sub spl infin control where necessary and sufficient conditions were obtained only sufficient condition based on lyapunov method is shown furthermore connection between robust h sub spl infin problems involving uncertainty and standard uncertainty free h sub spl infin problems is established via matrix algebra as for controller synthesis a state feedback fuzzy control law is designed via relaxed linear matrix inequality lmi formulations

delay dependent guaranteed cost control for t s fuzzy systems with time delays this study introduces a guaranteed cost control method for nonlinear systems with time delays which can be represented by takagi sugeno t s fuzzy models with time delays the state feedback and generalized dynamic output feedback approaches are considered the generalized dynamic output feedback controller is presented by a new fuzzy controller architecture which is of dual indexed rule base it considers both the dynamic part and the output part of t s fuzzy model which guarantees that the controller without any delay information can stabilize time delay t s fuzzy systems based on delay dependent lyapunov functional approach some sufficient conditions for the existence of state feedback controller are provided via parallel distributed compensation pdc first second the corresponding conditions are extended into the generalized dynamic output feedback closed loop system via so called generalized pdc technique the upper bound of time delay can be obtained using convex optimization such that the system can be stabilized for all time delays whose sizes are not larger than the bound the minimizing method is also proposed to search the suboptimal upper bound of guaranteed cost function the effectiveness of the proposed method can be shown by the simulation examples

dissipativity based sampled data control for fuzzy switched markovian jump systems in this paper the dissipativity based sampled data control problem is studied for fuzzy switched markovian jump systems fsmjs by considering the problem of the asynchronous switching caused by the subsystems switching occurred during the sampling intervals constructing novel time dependent lyapunov functional and using average dwell time adt approach sufficient mean square exponential stability criteria and strictly mathcal q s r gamma dissipativity criteria are proposed under the constraints on that the maximum sampling period is no larger than the dwell time between the transition rates switching instants meanwhile a relationship between adt and sampling period is revealed for fsmjs based on the strictly mathcal q s r gamma dissipativity criteria the sampled data controller is designed for fsmjss a circuit simulation example is provided to illustrate the effectiveness of the proposed method

comments on robust stabilization of a class of uncertain nonlinear systems via fuzzy control quadratic stabilizability h sup spl infin control theory and linear matrix inequalities this paper presents stability analysis for a class of uncertain nonlinear systems and a method for designing robust fuzzy controllers to stabilize the uncertain nonlinear systems first a stability condition for takagi and sugeno s fuzzy model is given in terms of lyapunov stability theory next new stability conditions for a generalized class of uncertain systems are derived from robust control techniques such as quadratic stabilization h sup spl infin control theory and linear matrix inequalities the derived stability conditions are used to analyze the stability of takagi and sugeno s fuzzy control systems with uncertainty which can be regarded as a generalized class of uncertain nonlinear systems the design method employs the so called parallel distributed compensation important issues for the stability analysis and design are remarked finally three design examples of fuzzy controllers for stabilizing nonlinear systems and uncertain nonlinear systems are presented

dynamics and computation of continuous attractors continuous attractor is a promising model for describing the encoding of continuous stimuli in neural systems in a continuous attractor the stationary states of the neural system form a continuous parameter space on which the system is neutrally stable this property enables the neutral system to track time varying stimuli smoothly but it also degrades the accuracy of information retrieval since these stationary states are easily disturbed by external noise in this work based on a simple model we systematically investigate the dynamics and the computational properties of continuous attractors in order to analyze the dynamics of a large size network which is otherwise extremely complicated we develop a strategy to reduce its dimensionality by utilizing the fact that a continuous attractor can eliminate the noise components perpendicular to the attractor space very quickly we therefore project the network dynamics onto the tangent of the attractor space and simplify it successfully as a one dimensional ornstein uhlenbeck process based on this simplified model we investigate 1 the decoding error of a continuous attractor under the driving of external noisy inputs 2 the tracking speed of a continuous attractor when external stimulus experiences abrupt changes 3 the neural correlation structure associated with the specific dynamics of a continuous attractor and 4 the consequence of asymmetric neural correlation on statistical population decoding the potential implications of these results on our understanding of neural information processing are also discussed

robust h fuzzy static output feedback control of t s fuzzy systems with parametric uncertainties this paper addresses robust h fuzzy static output feedback control problem for t s fuzzy systems with time varying norm bounded uncertainties sufficient conditions for synthesis of a fuzzy static output feedback controller for t s fuzzy systems are derived in terms of a set of linear matrix inequalities lmis in comparison with the existing literatures the proposed approach not only simplifies the design procedure but also achieves a better h performance three drawbacks existing in the previous papers such as coordinate transformation same output matrices and bmi problem have been eliminated the effectiveness of the proposed design method is demonstrated by an example for the control of a truck trailer system

stability analysis and design of fuzzy control systems abstract the stability analysis and the design technique of fuzzy control systems using fuzzy block diagrams are discussed first we show the concept of fuzzy blocks and consider the connection problems of fuzzy blocks diagrams we derive some theorems and corollaries with respect to two basic types of connections of fuzzy blocks in order to preserve some properties in a connection of fuzzy blocks continuous piecewise polynomial membership functions are defined secondly a sufficient condition which guarantees the stability of fuzzy systems is obtained in terms of lyapunov s direct method we give an important fact based on this condition thirdly we propose a new design technique of a fuzzy controller the fuzzy block diagrams and the stability analysis are applied to the design problems of a model based fuzzy controller

reciprocally convex approach to stability of systems with time varying delays whereas the upper bound lemma for matrix cross product introduced by park 1999 and modified by moon park kwon and lee 2001 plays a key role in guiding various delay dependent criteria for delayed systems the jensen inequality has become an alternative as a way of reducing the number of decision variables it directly relaxes the integral term of quadratic quantities into the quadratic term of the integral quantities resulting in a linear combination of positive functions weighted by the inverses of convex parameters this paper suggests the lower bound lemma for such a combination which achieves performance behavior identical to approaches based on the integral inequality lemma but with much less decision variables comparable to those based on the jensen inequality lemma

maximal multiplicities in cocharacter sequences if a is a p i algebra mn a is the maximum multiplicity of the sn irreducible characters in the nth cocharacter of a we prove that if 1 a then mn a is asymptotic to a polynomial and we compute the degree of this polynomial for the verbally prime p i algebras

asymptotics in cocharacters of simple algebras with involution abstract we compute the asymptotics of the colength and maximal multiplicity sequences of simple algebras with involution

brief paper wirtinger s inequality and lyapunov based sampled data stabilization discontinuous lyapunov functionals appeared to be very efficient for sampled data systems fridman 2010 naghshtabrizi hespanha teel 2008 in the present paper new discontinuous lyapunov functionals are introduced for sampled data control in the presence of a constant input delay the construction of these functionals is based on the vector extension of wirtinger s inequality these functionals lead to simplified and efficient stability conditions in terms of linear matrix inequalities lmis the new stability analysis is applied to sampled data state feedback stabilization and to a novel sampled data static output feedback problem where the delayed measurements are used for stabilization

network based fuzzy control for nonlinear markov jump systems subject to quantization and dropout compensation abstract this paper focuses on the issue of network based fuzzy control for nonlinear markov jump systems with unreliable communication links the nonlinear system under consideration is described by a takagi sugeno t s fuzzy model through corresponding fuzzy rules the control signals are quantized by a logarithmic quantizer before they are transmitted to the network and in case quantized control signals lose intermittently when being passed to the actuator a compensation strategy is implemented to deal with the packet dropout based on a novel lyapunov function which is both fuzzy basis dependent and mode dependent the existence criterion for the desired controller is established to ensure the stochastic stability as well as a predefined h performance index of the resulting closed loop system a bench mark example of robot arm is presented to demonstrate the validity of the proposed design technique

fuzzy guaranteed cost control for nonlinear systems with time varying delay this paper focuses on the problem of guaranteed cost control for takagi sugeno t s fuzzy systems with time varying delayed state a linear quadratic cost function is considered as a performance index of the closed loop fuzzy system then the guaranteed cost control of the closed loop fuzzy system is discussed and the sufficient conditions are provided for the construction of a guaranteed cost controller via state feedback and observer based output feedback when these conditions which are given in terms of the feasibility of linear matrix inequalities lmis are satisfied the designed state feedback controller and observer based controller gain matrices can be obtained via a convex optimization problem two illustrative examples are provided to demonstrate the effectiveness of the approaches proposed in this paper

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

effects of synaptic depression and adaptation on spatiotemporal dynamics of an excitatory neuronal network we analyze the spatiotemporal dynamics of a system of integro differential equations that describes a one dimensional excitatory neuronal network with synaptic depression and spike frequency adaptation physiologically suggestive forms are used for both types of negative feedback we also consider the effects of employing two different types of firing rate function a heaviside step function and a piecewise linear function we first derive conditions for the existence of traveling fronts and pulses in the case of a heaviside step firing rate and show that adaptation plays a relatively minor role in determining the characteristics of traveling waves we then derive conditions for the existence and stability of stationary pulses or bumps and show that a purely excitatory network with synaptic depression cannot support stable bumps however bumps do not exist in the presence of adaptation finally in the case of a piecewise linear firing rate function we show numerically that the network also supports self sustained oscillations between an up state and a down state in which a spatially localized oscillating core periodically emits pulses at each cycle

fuzzy model based reliable static output feedback mathscr h _ infty control of nonlinear hyperbolic pde systems this paper investigates the problem of output feedback robust mathscr h infty control for a class of nonlinear spatially distributed systems described by first order hyperbolic partial differential equations pdes with markovian jumping actuator faults the nonlinear hyperbolic pde systems are first expressed by takagi sugeno fuzzy models with parameter uncertainties and then the objective is to design a reliable distributed fuzzy static output feedback controller guaranteeing the stochastic exponential stability of the resulting closed loop system with certain mathscr h infty disturbance attenuation performance based on a markovian lyapunov functional combined with some matrix inequality convexification techniques two approaches are developed for reliable fuzzy static output feedback controller design of the underlying fuzzy pde systems it is shown that the controller gains can be obtained by solving a set of finite linear matrix inequalities based on the finite difference method in space finally two examples are presented to demonstrate the effectiveness of the proposed methods

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

stability and stabilization of takagi sugeno fuzzy systems via sampled data and state quantized controller in this paper we investigate the problem of stability and stabilization for sampled data fuzzy systems with state quantization by using an input delay approach the sampled data fuzzy systems with state quantization are transformed into a continuous time system with a delay in the state the transformed system contains nondifferentiable time varying state delay based on some integral techniques some new stability and stabilization criteria are first proposed by a modified lyapunov functional furthermore in the case of no quantization some new stability and stabilization criteria are also obtained it is shown that the new stability and stabilization criteria can provide a larger upper bound of the sampling interval than some existing ones in the literature two simulation examples are given to show the effectiveness of the proposed design method

delay dependent robust h sub spl infin control for t s fuzzy systems with time delay this paper focuses on the problem of delay dependent robust fuzzy control for a class of nonlinear delay systems via state feedback the takagi sugeno t s fuzzy model is adopted for representing a nonlinear system with time delayed state a delay dependent stabilization criterion is first presented then the methods of robust stabilization and robust h sub spl infin control are developed which are dependent on the size of the delay and are based on the solutions of linear matrix inequalities lmis finally a design example of robust h sub spl infin controller for uncertain nonlinear systems is given to illustrate the effectiveness of the approaches proposed in this paper

robust h_ infty control for uncertain takagi sugeno fuzzy systems with interval time varying delay this paper is concerned with the problem of robust hinfin control for a class of uncertain time delay fuzzy systems the time delay is assumed to be a time varying continuous function belonging to a given interval which means that the lower and upper bounds for the time varying delay are available no restriction on the derivative of the time varying delay is needed which allows the time delay to be a fast time varying function the takagi sugeno t s uncertain fuzzy model with interval time varying delay is adopted based on the lyapunov krasovskii functional approach some delay dependent conditions for the existence of robust hinfin controller are formulated in the form of linear matrix inequalities lmis when these lmis are feasible an hinfin controller is presented a numerical example is given to demonstrate the effectiveness of the proposed method

an approach to h control of fuzzy dynamic systems this paper presents an approach to h control of a class of continuous time nonlinear systems which can be represented by a fuzzy dynamic model a suitable piecewise differentiable quadratic lyapunov function is used to establish asymptotic stability and h performance of the closed loop fuzzy control system a constructive algorithm is developed to obtain the h feedback control law which involves solving a set of suitable algebraic riccati equations an example is given to illustrate the application of the method

spontaneous motion on two dimensional continuous attractors attractor models are simplified models used to describe the dynamics of firing rate profiles of a pool of neurons the firing rate profile or the neuronal activity is thought to carry information continuous attractor neural networks canns describe the neural processing of continuous information such as object position object orientation and direction of object motion recently it was found that in one dimensional canns short term synaptic depression can destabilize bump shaped neuronal attractor activity profiles in this article we study two dimensional canns with short term synaptic depression and spike frequency adaptation we found that the dynamics of canns with short term synaptic depression and canns with spike frequency adaptation are qualitatively similar we also found that in both kinds of canns the perturbative approach can be used to predict phase diagrams dynamical variables and speed of spontaneous motion

stabilization of chaotic systems under variable sampling and state quantized controller abstract this paper investigates the problem of stabilization for chaotic systems based on a t s fuzzy model under sampled data control and state quantization a novel lyapunov krasovskii functional lkf is introduced to the sampled data systems the benefit of the new approach is that the lkf develops more information about the actual sampling pattern in addition some symmetric matrices involved in the lkf are not required to be positive definite based on a recently introduced wirtinger based integral inequality that has been shown to be less conservative than jensen s inequality much less conservative stabilization conditions are obtained to ensure the maximal sampling period then the corresponding sampled data controllers can be synthesized by solving a set of linear matrix inequalities lmis finally an illustrative example is given to show the feasibility and effectiveness of the proposed method

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

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

on relaxed lmi based designs for fuzzy regulators and fuzzy observers relaxed conditions for stability of nonlinear continuous and discrete time systems given by fuzzy models are presented a theoretical analysis shows that the proposed methods provide better or at least the same results of the methods presented in the literature numerical results exemplify this fact these results are also used for fuzzy regulators and observers designs the nonlinear systems are represented by fuzzy models proposed by takagi and sugeno 1985 the stability analysis and the design of controllers are described by linear matrix inequalities that can be solved efficiently using convex programming techniques the specification of the decay rate constrains on control input and output are also discussed

network based robust passive control for fuzzy systems with randomly occurring uncertainties this paper investigates the problem of robust passive control for networked fuzzy systems where randomly occurring uncertainties variable sampling intervals and constant network induced delay are taken into account a discontinuous lyapunov functional is introduced for the closed loop systems which takes full advantage of the sawtooth structure of the time varying interval delay induced by sample and hold and signal transmission a sufficient condition is proposed to ensure the closed loop system to be robustly stochastically passive then the problem of robust passive control is solved two examples are utilized to illustrate the advantages and effectiveness of the results that are proposed in this paper

design of h control for fuzzy time delay systems abstract in this paper the design problems of h output feedback controllers for takagi sugeno fuzzy time delay systems are considered we first introduce takagi sugeno fuzzy time delay systems and the h performance norm for stable fuzzy time delay systems we consider systems with multiple time delays in state we give a sufficient condition for the norm being less than a given number we then consider the h problems with output feedback controllers both memoryless controller and controller with memory are considered in the design of output feedback controllers the selection of the premise variables in the if then rules is important as for the premise variable we consider three cases where the premise variable is a given function the output and the state of the underlying system in the first two cases we give a design method of h controllers and sufficient conditions which guarantee the required h performance of the closed loop system in the last case we give an h controller for an approximation of the original system two examples are given to illustrate the theory