t s fuzzy model based piecewise h output feedback controller design for networked nonlinear systems with medium access constraint abstract this paper investigates the problem of h output feedback control for a class of networked nonlinear systems subject to medium access constraint where the nonlinear systems are represented by takagi sugeno t s fuzzy models with norm bounded uncertainties the communication constraint concerned is that only one sensor node and one actuator node can access the shared network which is the case in network environment the accessibility of sensor nodes and or actuator nodes is determined by medium access control with a prescribed probability the attention is focused on the design of a piecewise static output feedback controller such that the closed loop control system is stochastically stable with a guaranteed h performance based on piecewise quadratic lyapunov functions together with some matrix inequality convexifying techniques an approach to the design of h output feedback controller is proposed in terms of linear matrix inequalities finally two simulation examples are provided to illustrate the effectiveness of the proposed methods

modeling identification and control of a class of nonlinear systems in this paper we propose a new fuzzy hyperbolic model for a class of complex systems which is difficult to model the fuzzy hyperbolic model is a nonlinear model in nature and can be easily derived from a set of fuzzy rules it can also be seen as a feedforward neural network model and so we can identify the model parameters by bp algorithm we prove that the stable controller can be designed based on linear system theory two methods of designing the controller for the fuzzy hyperbolic model are proposed the results of simulation support the effectiveness of the model and the control scheme

restoration of a discrete time signal segment by interpolation based on the left sided and right sided autoregressive parameters this paper presents an algorithm for the interpolation of a missing signal segment on the assumption that the signal can be modeled as an autoregressive ar process unlike previous algorithms the presented algorithm does not model the signal of the missing segment and the neighboring signal portions by a single ar parameter vector instead two separate vectors are used so that stationarity need no longer be assumed to extend beyond both sides of the missing segment the relaxation of this stationarity assumption is essential when the duration of the missing segment is on the order of the short time stationarity duration of the signal the algorithm provides the optimal solution to the problem of interpolating a missing segment based on the left sided and right sided ar parameter vectors the solution is optimal in the sense of a least squares residual the algorithm is applied to speech and music signals and is compared with other restoration techniques

event triggered fuzzy h control for a class of nonlinear networked control systems using the deviation bounds of asynchronous normalized membership functions this paper is concerned with the event triggered h control for a nonlinear networked control system a new event triggered transmission scheme is first proposed to reduce the network bandwidth utilization under this scheme the nonlinear networked control system is formulated as a takagi sugeno fuzzy threshold error dependent system with asynchronous normalized membership functions then by using the deviation bounds of asynchronous normalized membership functions some sufficient conditions on the existence of the parameters of the event triggered transmission scheme and the fuzzy controller are derived such that the takagi sugeno fuzzy threshold error dependent system with asynchronous normalized membership functions is asymptotically stable with a prescribed h attenuation level it is shown that the proposed design method can reduce the conservativeness of some existing results finally two examples are given to demonstrate the effectiveness of the proposed design method and the event triggered transmission scheme

h quantized control for nonlinear networked control systems this paper presents a new approach to the problems of h analysis and synthesis for nonlinear networked control systems nncss with limited communication capacity where a nncs can be represented by a t s fuzzy model with two time varying quantizers neither free weighting matrices nor model transformations are employed in the derivation instead by constructing an improved lyapunov function and introducing an extended jessen s inequality an improved stability criteria is obtained the h controller is shown in terms of nonlinear matrix inequalities which can be computed through solving a convex optimization problem numerical examples are exploited to show the usefulness and effectiveness of the results obtained

quantized output feedback control for networked control systems this paper addresses the problem of output feedback control for networked control systems ncss with limited communication capacity firstly we propose a new model to describe the non ideal network conditions and the input output state quantization of the ncss in a unified framework secondly based on our newly proposed model and an improved separation lemma the observer based controller is developed for the asymptotical stabilization of the ncss which are shown in terms of nonlinear matrices inequalities the nonlinear problems can be computed through solving a convex optimization problems and the observed and controller gains could be derived by solving a set of linear matrix inequalities thirdly two simulation examples are given to demonstrate the effectiveness of the proposed method

qr decomposition based least squares lattice interpolators qr decomposition based least squares lattice qrd lsl predictors have been extensively applied in the design of order recursive adaptive filters this work presents qrd lsl interpolators that use both past and future data samples to estimate the present data sample based on a novel decoupling property we show that the order recursive qrd lsl interpolators display better numerical properties and achieve a higher level of computational efficiency than the conventional lsl interpolators except for an overall delay needed for physical realization qrd lsl interpolators can substantially outperform qrd lsl predictors while retaining all the desirable features of the latter

asymmetric interpolation lattice this paper presents a new lattice structure for linear interpolation the interpolation lattice structure is asymmetric in the sense that the number of past and future values linearly weighted to estimate the current value does not have to be identical the lattice structure provides a computationally efficient and structurally flexible realization for the interpolation lattice it also leads to a generalization of the concepts of the well known linear prediction lattice and symmetric interpolation lattice

network based output tracking control for t s fuzzy systems using an event triggered communication scheme this paper is concerned with network based output tracking control for a t s fuzzy system an event triggered communication scheme under which the threshold depends on the latest successfully transmitted sampled data is introduced to reduce network resource utilization taking the event triggered communication scheme and the asynchronous operation between the fuzzy system and the fuzzy controller the resulting system is modeled as an asynchronous threshold error dependent system with an interval time varying delay a new delay dependent criterion for l 2 gain tracking performance of the asynchronous system is derived by applying the deviation bounds of asynchronous normalized membership functions based on this performance criterion some criteria on the existence of the fuzzy tracking controller are established a co design algorithm is presented to obtain the control gains and the event triggering parameters simultaneously an example is given to illustrate the effectiveness of the proposed method

linear interpolation lattice the analysis and synthesis filters of linear prediction theory are extended to include linear interpolation a noncausal lattice filter for linear interpolation is obtained from the linear interpolation recursion the results provide insight into the interrelation of prediction and interpolation and of one and two sided representations of one dimensional markov sequences

some results in linear interpolation theory using a well known form for the inverse of a symmetric toeplitz matrix some results in linear interpolation theory are derived for an autoregressive process it is shown that interpolation at the mid point of a data record yields the minimum interpolation error also some results for infinite length interpolators are simply derived

nonlinear infinite extent interpolation of stationary processes the problem of minimum mean square interpolation of discrete time stationary stochastic processes using a system consisting of a finite number p of nonlinear instantaneous transformations followed by a p input one output infinite extent linear filter is studied the expressions of the optimal interpolator and of the approximation error are derived and generalize the corresponding relations known in linear interpolation theory some extensions including the estimation problem with several missing observations are also investigated

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

technical communique absolute stability of time delay systems with sector bounded nonlinearity this paper deals with the problem of absolute stability of time delay systems with sector bounded nonlinearity some new delay dependent stability criteria are obtained and formulated in the form of linear matrix inequalities lmis neither model transformation nor bounding technique for cross terms is involved through derivation of the stability criteria numerical examples show that the results obtained in this paper improve the estimate of the stability limit over some existing result

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

some properties of prediction and interpolation errors linear prediction and interpolation are widely used in signal processing usually they are obtained by linear filters of finite memory and the prediction and interpolation errors decrease when this memory increases if the asymptotic values of these errors are null the signal is singular some theoretical aspects of finite and infinite prediction and interpolation are discussed and a numerical method to compute the prediction and interpolation errors for signals with a given power spectrum is presented a large number of results obtained with this method are discussed especially the difference between regular and singular signals this method also allows the behavior of prediction and interpolation errors when the memory of the filter increases to be studied

a novel dropout compensation scheme for control of networked t s fuzzy dynamic systems this paper considers the problem of h state feedback control for networked nonlinear systems under unreliable communication links with packet dropouts the nonlinear plant in this paper is described by a takagi sugeno t s fuzzy model the packet dropouts in both sensor to controller s c and controller to actuator c a channels are considered which are modeled by bernoulli processes a new compensation scheme for the estimation of missing packets is proposed and a piecewise state feedback controller is designed so that the resulting closed loop control system is stochastically stable with guaranteed h performance then the results are extended to the case when both network induced delays and packet dropouts exist in communication links finally some numerical examples are given to illustrate the procedure of the proposed approaches and the optimal h performance in comparison to the existing approaches

optimal fir pre and postfilters for decimation and interpolation of random signals a technique for the design of finite impulse response fir filters for decimation and interpolation in multirate systems is introduced fir prefilters and postfilters that jointly minimize a frequency weighted mean square error between the original and reconstructed signals can be designed there is no need for ideal filter prototypes the optimal pre postfilter pair is determined from the signal and noise spectra and the up sampling and down sampling factors some examples of image and speech processing show that the mean square optimal filter pair leads to typical snr improvements of 2 6 db in comparison to other commonly used filters

input to state stability of networked control systems a new class of lyapunov uniformly globally asymptotically stable ugas protocols in networked control systems ncs is considered it is shown that if the controller is designed without taking into account the network so that it yields input to state stability iss with respect to external disturbances not necessarily with respect to the error that will come from the network implementation then the same controller will achieve semi global practical iss for the ncs when implemented via the network with a lyapunov ugas protocol moreover the iss gain is preserved the adjustable parameter with respect to which semi global practical iss is achieved is the maximal allowable transfer interval mati between transmission times

robust h control of takagi sugeno fuzzy systems with state and input time delays this paper addresses the robust h fuzzy control problem for nonlinear uncertain systems with state and input time delays through takagi sugeno t s fuzzy model approach the delays are assumed to be interval time varying delays and no restriction is imposed on the derivative of time delay based on lyapunov krasoviskii functional method delay dependent sufficient conditions for the existence of an h controller are proposed in linear matrix inequality lmi format illustrative examples are given to show the effectiveness and merits of the proposed fuzzy controller design methodology

mode independent fuzzy fault tolerant variable sampling stabilization of nonlinear networked systems with both time varying and random delays this paper develops a fault tolerant variable sampling control vsc scheme for a class of nonlinear networked control systems ncss with time varying state and random network delays an uncertain continuous takagi sugeno t s fuzzy system with both state and input varying delays in the presence of possible actuator faults is obtained equivalently on the basis of the input delay methodology a tighter bounding lemma is proposed so as to gain less conservative closed loop stability criteria delay dependent conditions in terms of linear matrix inequalities are derived for the mode independent fault tolerant stabilizing controller of the resulting markovian network based system by employing a novel stochastic lyapunov krasovskii l k functional an illustrative example is simulated to show the validity of the obtained results

interpolation of complex stationary processes the problem of minimum mean square infinite extent interpolation for discrete time stationary complex stochastic processes is studied the interpolator consists of linear combinations of samples of the process and of their complex conjugate the expressions of the interpolator and of the approximation error are derived and various consequences are examined it is shown in particular that the approximation error may be zero while the interpolation error obtained when using only linear combinations of the samples is maximum