brief paper control for discrete singular hybrid systems the problems of stability state feedback control and static output feedback control for a class of discrete time singular hybrid systems are investigated in this paper a new sufficient and necessary condition for a class of discrete time singular hybrid systems to be regular causal and stochastically stable is proposed in terms of a set of coupled strict linear matrix inequalities lmis sufficient conditions are proposed for the existence of state feedback controller and static output feedback controller in terms of a set of coupled strict lmis respectively finally two illustrative examples are provided to demonstrate the applicability of the proposed approach

solution of the h sub infinity optimal linear filtering problem for discrete time systems the solution of l sub 2 minimum variance and h sub infinity estimation problems is considered using a polynomial systems approach the results for the l sub 2 filtering problem which corresponds with wiener or kalman filtering prediction are first presented in polynomial matrix form attention then turns to the solution of the h sub infinity estimation problem for scalar systems numerous examples are presented to illustrate the computational procedures the two types of estimator are appropriate to very different estimation problems and the new h sub infinity devices should be valuable in certain application areas

the projective method for solving linear matrix inequalities numerous problems in control and systems theory can be formulated in terms of linear matrix inequalities lmi since solving an lmi amounts to a convex optimization problem such formulations are known to be numerically tractable however the interest in lmi based design techniques has really surged with the introduction of efficient interior point methods for solving lmis with a polynomial time complexity this paper describes one particular method called the projective method simple geometrical arguments are used to clarify the strategy and convergence mechanism of the projective algorithm a complexity analysis is provided and applications to two generic lmi problems feasibility and linear objective minimization are discussed

feedback and pole placement in descriptor variable systems the effects and uses of applying linear feedback to continuous time descriptor systems are studied structural changes resulting from feeding back the slow and fast parts of the trajectory separately are characterized it is shown that under certain conditions related to controllability the poles of the slow subsystem may be shifted arbitrarily and the impulsive behaviour of the fast subsystem may be eliminated

h control for descriptor systems a matrix inequalities approach abstract this paper considers the h control problem for descriptor systems that possibly have impulsive modes and or j axis zeros first we propose matrix inequalities that give a generalized stability condition and an h norm condition for descriptor systems using these matrix inequalities we show that the solvability of a set of matrix inequalities is necessary and sufficient to the existence of a proper controller that satisfies a prescribed h norm condition as well as stabilizing the closed loop system and eliminating all impulsive modes these inequalities are equivalent to certain linear matrix inequalities to which we can get solutions whenever they exist using efficient polynomial time algorithms

fault detection filter design for markovian jump singular systems with intermittent measurements this paper addresses the problem of fault detection filter design for discrete time markovian jump singular systems with intermittent measurements the measurement transmission from the plant to the fault detection filter is assumed to be imperfect and a stochastic variable is utilized to model the phenomenon of data missing our attention is focused on the design of a fault detection filter such that the residual system is stochastically markovian jump admissible and satisfies some expected performances a new necessary and sufficient condition for a class of discrete time markovian jump singular systems to be stochastically markovian jump admissible is proposed in the form of strict linear matrix inequalities sufficient conditions are established for the existence of the fault detection filter finally a numerical example is provided to demonstrate the usefulness and applicability of the developed theoretical results

brief paper h filtering for rectangular discrete time descriptor systems this paper deals with the h recursive estimation problem for general rectangular time variant descriptor systems in discrete time riccati equation based recursions for filtered and predicted estimates are developed based on a data fitting approach and game theory in this approach the nature determines a state sequence seeking to maximize the estimation cost whereas the estimator tries to find an estimate that brings the estimation cost to a minimum a solution exists for a specified c level if the resulting cost is positive in order to present some computational alternatives to the h filters developed they are rewritten in information form along with the respective array algorithms

an lmi approach to periodic discrete time unbiased filtering the problem of unbiased filtering for a discrete time linear periodic system is faced by means of linear matrix inequality techniques as leading case we derive the synthesis conditions to obtain an unbiased filter and an unbiased fixed lag smoother enforcing a bound on the h performance on the error dynamics

brief paper design of h filter for markov jumping linear systems with non accessible mode information for markov jumping linear systems mjls it is often encountered that the jumping mode cannot be accessible for filtering therefore it is strongly desirable to design a filter which is independent of the jumping model in this paper a new deterministic filter design procedure is proposed which shows less conservatism than existing results the whole design procedure can be accomplished by solving a set of linear matrix inequalities lmis finally numerical examples are given to illustrate the effectiveness of the proposed approach

interpolation approach to h estimation and its interconnection to loop transfer recovery abstract this paper proposes to solve the h optimal estimation problem via interpolation theory the advantages of this approach are the following i direct and simple solutions can be obtained for the optimal estimators ii frequency weightings on estimation error and disturbance can be easily incorporated and iii unnecessary high observer gains can be avoided we also show the interconnection between the h optimal estimation problem and the optimal loop transfer recovery problem the interpolation approach applies to both continuous time and discrete time systems

h sub spl infin state feedback control for discrete singular systems deals with the problem of state feedback h sub spl infin control for discrete singular systems it is not assumed that the singular system under consideration is necessarily regular the problem we address is the design of a state feedback controller such that the resulting closed loop system is not only regular causal and stable but also satisfies a prescribed h sub spl infin norm bound condition in terms of certain matrix inequalities a necessary and sufficient condition for the solution to this problem is obtained and a suitable state feedback control law is also given

general solutions of the narrow strip and slot integral equations analytic solutions of the integral equations for the current induced on a narrow conducting strip are obtained by two methods one method follows from an expansion of the strip current in a series of chebyshev polynomials while the other is based on a special power series expansion in the former fourier type coefficients depending on integrals of the excitation are derived while in the latter the coefficients depend upon derivatives of the excitation from knowledge of the strip current simple expressions for the far zone scattered field are derived explicit results are given for plane wave excitation the solution methods apply to the equations for the narrow slot in a planar conducting screen

subspace based estimation of time delays and doppler shifts this paper considers the problem of estimating the time delays and doppler shifts of a known waveform received via several distinct paths by an array of antennas the general maximum likelihood estimator is presented and is shown to require a 2d dimensional nonlinear minimization where d is the number of received signal reflections two alternative solutions based on signal and noise subspace fitting are proposed requiring only a d dimensional minimization in particular we show how to decouple the required search into a two step procedure where the delays are estimated and the dopplers solved for explicitly initial conditions for the time delay search can be obtained by applying generalizations of the music and esprit algorithms which are also outlined in the paper simulation examples are included to illustrate the algorithms performance relative to the cramer rao bound

h_ infty positive filtering for positive linear discrete time systems an augmentation approach in this note we address the reduced order positive filtering problem of positive discrete time systems under the h performance commonly employed approaches such as linear transformation and elimination technique may not be applicable in general due to the positivity constraint of the filter to cope with the difficulty we first represent the filtering error system as a singular system by means of the system augmentation approach which will facilitate the consideration of the positivity constraint two necessary and sufficient conditions are obtained in terms of matrix inequalities under which the filtering error system has a prescribed h performance then a necessary and sufficient condition is proposed for the existence of the desired positive filters and an iterative linear matrix inequality lmi algorithm is presented to compute the filtering matrices which can be easily checked by standard software finally a numerical example to illustrate the effectiveness of the proposed design procedures is presented

observer based beamforming algorithm for acoustic array signal processing in the field of noise identification with microphone arrays conventional delay and sum das beamforming is the most popular signal processing technique however acoustic imaging results that are generated by das beamforming are easily influenced by background noise particularly for in situ wind tunnel tests even when arithmetic averaging is used to statistically remove the interference from the background noise the results are far from perfect because the interference from the coherent background noise is still present in addition das beamforming based on arithmetic averaging fails to deliver real time computational capability an observer based approach is introduced in this paper this so called observer based beamforming method has a recursive form similar to the state observer in classical control theory thus holds a real time computational capability in addition coherent background noise can be gradually rejected in iterations theoretical derivations of the observer based beamforming algorithm are carefully developed in this paper two numerical simulations demonstrate the good coherent background noise rejection and real time computational capability of the observer based beamforming which therefore can be regarded as an attractive algorithm for acoustic array signal processing

brief paper delay dependent robust h filtering for uncertain discrete time singular systems with interval time varying delay this paper focuses on the delay dependent robust h filtering for uncertain discrete time singular systems with interval time varying delay the uncertainty considered is a convex compact set of polytopic type the purpose is the design of a linear robust h filter such that the resulting filtering error singular system is regular causal and asymptotically stable with a h norm bound by establishing a finite sum inequality based on quadratic terms a new delay dependent bounded real lemma brl for delayed singular systems is derived based on the derived brl a sufficient condition for the solvability of this problem is obtained in terms of linear matrix inequality lmi without decomposing the original system matrices also it is shown that the proposed filter design method is general for both singular systems and non singular systems finally illustrative examples are presented to show the applicability of the proposed method

new results on h filtering for fuzzy systems with interval time varying delays this paper investigates the problem of h filtering for continuous takagi sugeno t s fuzzy systems with an interval time varying delay in the state based on the delay partitioning idea a new approach is proposed for solving this problem which can achieve much less conservative feasibility conditions the attention is focused on the design of an h filter via the parallel distributed compensation scheme such that the filter error system is asymptotically stable and the h attenuation level from disturbance to estimation error is below a prescribed scalar the constructed lyapunov krasovskii functional by applying the delay partitioning method can potentially guarantee the obtained delay dependent conditions to be less conservative than those in the literature the obtained results are formulated in the form of linear matrix inequalities lmis which can be readily solved via standard numerical software finally an example is illustrated to show the reduction in conservatism of the proposed filter design method

current induced on a conducting strip which resides on the planar interface between two semi infinite half spaces an analysis is described for determining the current induced by a known excitation on a conducting strip which resides on the planar interface between two semi infinite homogeneous half spaces of different electromagnetic properties the perfectly conducting flat strip is of infinite extent and the excitation is transverse magnetic to the strip axis an integral equation for the induced current is formulated and it is shown that its kernel which is in general a sommerfeld type integral can be expressed in closed form when the permeabilities of the two media are the same under this practical condition the integral equation is solved numerically and data are presented for cases of interest for the electrically narrow strip the integral equation is approximated and this approximate equation is solved analytically

on state feedback h control for discrete time singular systems this technical note deals with the state feedback h control problem for linear time invariant discrete time singular systems relied on the use of auxiliary matrices and a positive scalar a novel necessary and sufficient condition for the bounded real lemma is derived for discrete time singular systems the characterization is reduced to a strict linear matrix inequality lmi when the scalar is fixed and the resulting lmi is non conservative as long as the scalar is chosen sufficiently large moreover the result is further expanded to h controller design and a numerically efficient and reliable design procedure is given since no particular restriction is imposed on the auxiliary matrices the proposed result outperforms the existing methods in the literature numerical examples are included to illustrate the effectiveness of the present result

bayes and empirical bayes semi blind deconvolution using eigenfunctions of a prior covariance we consider the semi blind deconvolution problem i e estimating an unknown input function to a linear dynamical system using a finite set of linearly related measurements where the dynamical system is known up to some system parameters without further assumptions this problem is often ill posed and ill conditioned we overcome this difficulty by modeling the unknown input as a realization of a stochastic process with a covariance that is known up to some finite set of covariance parameters we first present an empirical bayes method where the unknown parameters are estimated by maximizing the marginal likelihood posterior and subsequently the input is reconstructed via a tikhonov estimator with the parameters set to their point estimates next we introduce a bayesian method that recovers the posterior probability distribution and hence the minimum variance estimates for both the unknown parameters and the unknown input function both of these methods use the eigenfunctions of the random process covariance to obtain an efficient representation of the unknown input function and its probability distributions simulated case studies are used to test the two methods and compare their relative performance

h filtering for a class of uncertain nonlinear systems abstract this paper investigates the problem of h filtering for a class of uncertain continuous time nonlinear systems with real time varying parameter uncertainty and unknown initial state we develop an infinite horizon h filtering methodology which provides both robust stability and a guaranteed h performance for the filtering error irrespective of the parameter uncertainty

multiobjective h sub 2 h sub spl infin control for a linear time invariant system with several disturbance inputs and controlled outputs we show how to minimize the nominal h sub 2 norm performance in one channel while keeping bounds on the h sub 2 norm or h sub spl infin norm performance implying robust stability in the other channels this multiobjective h sub 2 h sub spl infin problem in an infinite dimensional space is reduced to sequences of finite dimensional convex optimization problems we show how to compute the optimal value and how to numerically detect the existence of a rational optimal controller if it exists we reveal how the novel trick of optimizing the trace norm of the youla parameter over certain convex constraints allows one to design a nearly optimal controller whose youla parameter is of the same order as the optimal one

h_ infty unbiased filtering for linear descriptor systems via lmi this note concerns the optimal h infin unbiased filtering problem for linear descriptor systems it unifies the design of reduced order minimal order and full order filters for continuous and discrete time systems necessary and sufficient conditions for the solvability of the problem are obtained in terms of a set of linear matrix inequalities lmis the parametrization of all h infin unbiased filters is presented application to standard systems with or without unknown inputs is given a numerical example is given to show the applicability of the presented approach

h sub infinity minimum error state estimation of linear stationary processes a state estimator is derived which minimizes the h sub infinity norm of the estimation error power spectrum matrix two approaches are presented the first achieves the optimal estimator in the frequency domain by finding the filter transfer function matrix that leads to an equalizing solution the second approach establishes a duality between the problem of h sub infinity filtering and the problem of unconstrained input h sub infinity optimal regulation using this duality previously published results for the latter regulation problem are applied which lead to an optimal filter that possess the structure of the corresponding kalman filter the two approaches usually lead to different results they are compared by a simple example which also demonstrates a clear advantage of the h sub infinity estimate over the conventional l sub 2 estimate

joint estimation of time delay and frequency delay in impulsive noise using fractional lower order statistics new methods for time delay estimation and joint estimation of time delay and frequency delay in the presence of impulsive noise are introduced first degradation of the conventional approaches based on second order statistics is shown both theoretically and experimentally then a new class of robust algorithms are developed using the theory of alpha stable distributions including the fractional lower order covariance floc method which is formulated for the time delay estimation problem and the fractional lower order ambiguity function floaf which is defined for the joint estimation of time delay and frequency delay it is shown that these new methods are robust for both gaussian and non gaussian impulsive noise environments the improved performance is clearly demonstrated through detailed analysis and comprehensive simulations with computer generated data as well as actual radar and sonar clutter data

h filtering via convex optimization this paper reformulates the suboptimal or level gamma h filtering problem into a linear matrix inequality lmi problem by applying a bounded real lemma to the closed loop transfer function this formulation not only provides the condition of solvability but also constructs the suboptimal h filter this formulation furthermore allows one to solve the epsilon optimal h filtering problem via convex optimization techniques where the epsilon optimality implies that theh norm of the resulting closed loop transfer function is greater than or equal to the infimum say gamma inf of the h norms of all possible closed loop transfer functions but is less than or equal to epsilon gamma for an extremely small positive number epsilon which will depend on the inf accuracy of the algorithms and the precision of a computer

current induced on a conducting cylinder located near the planar interface between two semi infinite half spaces an analysis is described for determining the current induced by a known excitation on a conducting cylinder located near the planar interface between two semi infinite homogeneous half spaces of different electromagnetic properties the perfectly conducting cylinder of general cross section is of infinite extent and the excitation is transverse magnetic to the cylinder axis an integral equations for the induced current is derived and a numerical method for solving it is developed the kernel of the integral equation contains a term corresponding to the usual open space green s function plus a term proportional to a sommerfeld type integral in two dimensions various forms of the sommerfeld type integral are given and the choices of form amenable to efficient evaluation are discussed for a flat strip a circular cylinder and a rectangular cylinder data are presented and discussed for selected parameters data are presented for cylinders above and below the interface as well as for a cylinder resting on the interface

joint estimation of time delays and directions of arrival of multiple reflections of a known signal we present an efficient algorithm for estimating the time delays and the directions of arrival doas of multiple reflections of a known signal the algorithm is based on an iterative scheme that transforms the multidimensional maximum likelihood criterion into two sets of simple one dimensional 1 d maximization problems simulation results illustrating the performance of the algorithm in comparison with the cramer rao bound are included

a linear matrix inequality approach to robust h sub spl infin filtering we consider the robust h sub spl infin filtering problem for a general class of uncertain linear systems described by the so called integral quadratic constraints iqcs this problem is important in many signal processing applications where noise nonlinearity quantization errors time delays and unmodeled dynamics can be naturally described by iqcs the main contribution of this paper is to show that the robust h spl infin filtering problem can be solved using linear matrix inequality lmi techniques which are numerically efficient owing to recent advances in convex optimization the paper deals with both continuous and discrete time uncertain linear systems

scattering of h polarized waves from conducting strips in the presence of an electrically uniaxial half space a singular integrodifferential equation approach electromagnetic scattering from perfectly conducting infinitely long strips in the presence of an electrically uniaxial half space is treated analytically a uniform h polarized plane wave is incident from the isotropic region as a prerequisite to this approach the h mode scalar green s function of the structure is developed its use in connection with the reciprocity theorem leads to a singular integrodifferential equation for the current density induced on the scatterer surface the equation is solved for strips parallel or perpendicular to the interface located above or embedded in the anisotropic region following a special technique based on the theory of singular integral equations that has been developed in connection with strips and slots and e or h polarized incident waves numerical results for the induced current density and for the scattered far field in a variety of cases are presented in graphical form whenever possible they are compared with existing results based on purely numerical procedures

h filter design for a class of nonlinear discrete time singular systems this paper deals with the h filter design problem for a class of discrete time lipschitz nonlinear singular systems the approach is based on the parameterisation of the obtained algebraic constraints from the estimation errors sufficient conditions for the existence of the filters which guarantee stability and the worst case filter error energy over all bounded energy disturbances is minimised are given the method also unifies the design for the full order reduced order minimal order filters for discrete time systems the presented results are less conservative than those existing in the literature this is due to the introduction of new slack variables application to systems with unknown input is presented via a numerical example

optimal cal h _ 2 filtering in networked control systems with multiple packet dropout this note studies the problem of optimal h2 filtering in networked control systems ncss with multiple packet dropout a new formulation is employed to model the multiple packet dropout case where the random dropout rate is transformed into a stochastic parameter in the system s representation by generalization of the h2 norm definition new relations for the stochastic norm of a linear discrete time stochastic parameter system represented in the state space form are derived the stochastic h2 norm of the estimation error is used as a criterion for filter design in the ncs framework a set of linear matrix inequalities lmis is given to solve the corresponding filter design problem a simulation example supports the theory

an algebraic riccati equation for the discrete time periodic prediction problem abstract in this paper the periodic problem is reformulated as a prediction problem relative to a suitable time invariant system this enables one to establish a one to one correspondence between the solutions of the discrete time periodic riccati equation dpre and the solutions of a suitable discrete time and time invariant riccati equation in particular the constant solutions of this last equation are the periodic generators of the original periodic riccati equation this enables one to easily derive existence uniqueness and convergence results for the drpe from known results relative to the time invariant case

information filtering and array algorithms for descriptor systems subject to parameter uncertainties this paper presents information filters in riccati recursions and in array algorithms for descriptor systems subject to parameters uncertainties the filters are developed in filtered and predicted forms the inversion of the state matrix is avoided in the new information recursive formulas therefore it turns out clear that the invertibility of the state matrix usually considered in the state space information recursions is not necessary a numerical example is provided to illustrate the performance of the proposed robust array algorithms

brief explicit formulas for lmi based h2 filtering and deconvolution this paper is concerned with the h 2 optimal estimation of a linear combination of the state and of the input of a discrete time linear time invariant dynamic system we reformulate such problem in terms of a set of three linear matrix inequalities lmi and we provide explicit formulas to compute a family of solutions for such lmis this family is explicitly parameterized by a real parameter e the h 2 performance of the corresponding filter may be rendered arbitrarily close to the optimum by choosing a sufficiently small e this procedure is shown to be computationally very efficient

time delay estimation for filtered poisson processes using an em type algorithm we develop a modified em algorithm to estimate a nonrandom time shift parameter of an intensity associated with an inhomogeneous poisson process n sub t whose points are only partially observed as a noise contaminated output x of a linear time invariant filter excited by a train of delta functions a filtered poisson process the exact em algorithm for computing the maximum likelihood time shift estimate generates a sequence of estimates each of which attempt to maximize a measure of similarity between the assumed shifted intensity and the conditional mean estimate of the poisson increment dn sub t we modify the em algorithm by using a linear approximation to this conditional mean estimate the asymptotic performance of the modified em algorithm is investigated by an asymptotic estimator consistency analysis we present simulation results that show that the linearized em algorithm converges rapidly and achieves an improvement over conventional time delay estimation methods such as linear matched filtering and leading edge thresholding in these simulations our algorithm gives estimates of time delay whose mean square error virtually achieves the cr lower bound for high count rates

brief paper h observers design for a class of nonlinear singular systems the present paper is devoted to the h observer or filter design problem for a class of lipschitz nonlinear singular systems the approach is based on the parameterization of the obtained algebraic constraints from the estimation errors sufficient conditions for the existence of the observers which guarantee stability and the worst case observers error energy over all bounded energy disturbances is minimized are given the method also unifies the design for the full order reduced order minimal order observers for continuous time systems it can be seen that the obtained conditions when applied to linear systems are also necessary a numerical example is given to show the applicability of our results

finite frequency h_ infty deconvolution with application to approximated bandlimited signal recovery this paper investigates a finite frequency h infty deconvolution problem for single input single output discrete time systems motivated by the fact that many practical signals are located in a finite frequency range this paper is focused on developing a design method for achieving better deconvolution performance over a finite frequency range first a finite frequency h infty deconvolution problem is formulated such that the deconvolution specification is characterized by a modified h mathbf infty index associated with the corresponding finite frequency range by an adapted generalized kalman yakubovich popov lemma and an auxiliary vector approach a matrix inequality condition is obtained for parameterizing a required deconvolution filter based on which a simple iterative algorithm is then constructed for optimizing the filter performance multiobjective deconvolution is further discussed in the same framework compared with the traditional frequency weighting strategy the proposed method can directly analyze and synthesize the deconvolution performance within finite frequency ranges the advantage of which is demonstrated in a bandlimited signal recovery example

reduced order h filtering for singular systems abstract this paper solves the problem of reduced order h filtering for singular systems the purpose is to design linear filters with a specified order lower than the given system such that the filtering error dynamic system is regular impulse free or causal stable and satisfies a prescribed h performance level one major contribution of the present work is that necessary and sufficient conditions for the solvability of this problem are obtained for both continuous and discrete singular systems these conditions are characterized in terms of linear matrix inequalities lmis and a coupling non convex rank constraint moreover an explicit parametrization of all desired reduced order filters is presented when these inequalities are feasible in particular when a static or zeroth order h filter is desired it is shown that the h filtering problem reduces to a convex lmi problem all these results are expressed in terms of the original system matrices without decomposition which makes the design procedure simple and directly last but not least the results have generalized previous works on h filtering for state space systems an illustrative example is given to demonstrate the effectiveness of the proposed approach

maximum likelihood estimation of liner signal parameters for poisson processes the estimation of linear signal parameters is studied under the hypothesis of independently poisson distributed measurements a simple interactive maximum likelihood estimator mle is derived and is optimized for rapid convergence it is shown to be statistically optimal in the sense of providing unbiased and minimum variance estimates experimental conditions are identified where mle results in significant performance improvement when compared to conventional linear least squares lls

optimal filtering with random sensor delay multiple packet dropout and uncertain observations this paper studies the problem of optimal filtering of discrete time systems with random sensor delay multiple packet dropout and uncertain observation the random sensor delay multiple packet dropout or uncertainty in observation is transformed to a stochastic parameter in the system representation a new formulation enables us to design an optimal filter for a system with multiple packet dropout in sensor data based on a stochastic definition of the norm of a system with a stochastic parameter new relations for stochastic norm are derived the stochastic norm of the estimation error is used as a criterion for the filter design the relations derived for the new norm definition are used to obtain a set of linear matrix inequalities lmis to solve the filter design problems simulation examples show the effectiveness of the proposed method

kalman filtering for general discrete time linear systems recursive state estimation problems for explicit and implicit time invariant linear systems both for systems with and without unknown inputs can be formulated as a single problem usually referred to as descriptor kalman filtering solutions to this problem have been proposed in the literature however these solutions either neglect possible contributions of future dynamics to the current estimate or make unnecessary assumptions on the structure of the system in this paper the authors propose a solution to this problem which leads to a constructive method lifting these unnecessary assumptions this method uses a generalization of the shuffle algorithm

technical communique reduced order delay dependent h filtering for uncertain discrete time singular systems with time varying delay in this paper a reduced order delay dependent robust h filter design method for uncertain discrete time singular systems with interval time varying delay is presented by the lmi approach on the basis of the bounded real lemma obtained we propose the sufficient condition for the existence of reduced order h filters such that the delayed filtering error singular system is regular causal and stable with h norm bound also a new reduced order h filter design method for discrete singular systems with lossy measurements is presented using the proposed method to show the applicability of the main result finally two numerical examples are provided to illustrate the applications of the reduced order filter design technique

optimal linear filtering under parameter uncertainty this paper addresses the problem of designing a guaranteed minimum error variance robust filter for convex bounded parameter uncertainty in the state output and input matrices the design procedure is valid for linear filters that are obtained from the minimization of an upper bound of the error variance holding for all admissible parameter uncertainty the results provided generalize the ones available in the literature to date in several directions first all system matrices can be corrupted by parameter uncertainty and the admissible uncertainty may be structured assuming the order of the uncertain system is known the optimal robust linear filter is proved to be of the same order as the order of the system in the present case of convex bounded parameter uncertainty the basic numerical design tools are linear matrix inequality lmi solvers instead of the riccati equation solvers used for the design of robust filters available in the literature to date the paper that contains the most important and very recent results on robust filtering is used for comparison purposes in particular it is shown that under the same assumptions our results are generally better as far as the minimization of a guaranteed error variance is considered some numerical examples illustrate the theoretical results

robust h sliding mode control for nonlinear stochastic t s fuzzy singular markovian jump systems with time varying delays abstract in this paper the robust h stabilization problem for stochastic t s fuzzy singular markovian jump systems with time delays is investigated by using integral sliding mode control a novel fuzzy integral type sliding surface function is designed by fully taking the singular derivative matrix into account by the utilization of linear matrix inequality technique a delay dependent criterion is derived which guarantees the sliding mode dynamics to be stochastically admissible with a prescribed h performance moreover a suitable sliding mode law is synthesized to ensure the stochastic admissibility of the resulting closed loop system and the proposed sliding mode control law can steer the trajectories of the controlled system to the specified sliding surface in finite time finally three examples are provided to illustrate the effectiveness of the proposed method

high resolution biosensor spectral peak shift estimation in this paper we present a maximum likelihood ml approach to high resolution estimation of the shifts of a spectral signal this spectral signal arises in application of optically based resonant biosensors where high resolution in the estimation of signal shift is synonymous with high sensitivity to biological interactions for the particular sensor of interest the underlying signal is nonuniformly sampled and exhibits poisson amplitude statistics shift estimation accuracies orders of magnitude finer than the sample spacing are sought the new ml based formulation leads to a solution approach different from typical resonance shift estimation methods based on polynomial fitting and peak or null estimation and tracking

robust output feedback controller design via local bmi optimization the problem of designing a globally optimal full order output feedback controller for polytopic uncertain systems is known to be a non convex np hard optimization problem that can be represented as a bilinear matrix inequality optimization problem for most design objectives in this paper a new approach is proposed to the design of locally optimal controllers it is iterative by nature and starting from any initial feasible controller it performs local optimization over a suitably defined non convex function at each iteration the approach features the properties of computational efficiency guaranteed convergence to a local optimum and applicability to a very wide range of problems furthermore a fast but conservative lmi based procedure for computing an initially feasible controller is also presented the complete approach is demonstrated on a model of one joint of a real life space robotic manipulator

reduced order h sub spl infin filtering for stochastic systems this paper deals with the reduced order h sub spl infin filtering problem for stochastic systems necessary and sufficient conditions are obtained for the existence of solutions to the continuous time and discrete time problems in terms of certain linear matrix inequalities lmis and a coupling nonconvex rank constraint condition furthermore when these conditions are feasible an explicit parametrization of all desired reduced order filters corresponding to a feasible solution is given in particular when the reduced order filter is restricted to be a static one then simple conditions expressed by lmis only without any rank constraints are derived and a parametrization of all solutions is also given finally an illustrative example is provided to show the effectiveness of the proposed approach

robustly asymptotically stable finite horizon mpc this paper presents a robustly stable finite horizon model predictive control mpc scheme for linear uncertain systems in which the uncertainty is not restricted to some specific uncertainty class polytopic affine lft etc the only requirement is that the state space matrices remain bounded over the uncertainty set suitable constraints are added to the mpc cost function to impose robust asymptotic stability and to deal with input output constraints the resulting optimization problem is solved at each time instant in a probabilistic framework using an iterative randomized ellipsoid algorithm rea the method is compared in simulation to the existing approach of kothare balakrishnan and morari 1996 robust constrained model predictive control using linear matrix inequalities automatica 32 10 1361 1379

exponential stability and interval stability of a class of stochastic hybrid systems driven by both brownian motion and poisson jumps abstract a class of stochastic singular hybrid systems driven by both brownian motion and poisson jumps are studied this paper is devoted to discussing the exponential stability and interval stability of such stochastic singular hybrid systems the concept of interval admissibility is proposed sufficient conditions are given for exponential mean square admissibility and interval admissibility by using ito s formula h representation and spectrum technique finally two simulation cases are presented to demonstrate the theoretical results

time delay and spatial signature estimation using known asynchronous signals this paper considers the problem of estimating the parameters of known signals received asynchronously by an array of antennas the parameters of primary interest are the time delays of the signals and their spatial signatures at the array estimates of the signal directions of arrival are also considered but are of secondary importance in this work maximum likelihood algorithms and more computationally efficient approximations are developed for both the case where all received signals are identical the channel estimation overlapping echo problem and where they are all distinct conditions are also derived under which the standard matched filter approach yields consistent and statistically efficient parameter estimates the issue of solution uniqueness is addressed and in particular an upper bound on the number of signals whose parameters may be uniquely identified is derived for a number of different cases typically the bound is far greater than the number of sensors and is limited only by the number of data samples collected some representative simulation examples are also included to illustrate the algorithms performance relative to the cramer rao bound

brief paper stability and stabilization of continuous time singular hybrid systems in this paper the problems of stability and state feedback stabilization for a class of continuous time singular hybrid systems are investigated a new sufficient and necessary condition for a continuous time singular hybrid system to be regular impulse free and stochastically stable is proposed in terms of a set of coupled strict linear matrix inequalities lmis moreover a new sufficient and necessary condition is presented for the existence of the state feedback controller in terms of a set of coupled strict matrix inequalities finally a numerical example is given to illustrate the effectiveness of the obtained theoretical results

filtering and smoothing in an h sup infinity setting the problems of filtering and smoothing are considered for linear systems in an h sup infinity setting i e the plant and measurement noises have bounded energies are in l sub 2 but are otherwise arbitrary two distinct situations for the initial condition of the system are considered the initial condition is assumed known in one case while in the other the initial condition is not known but the initial condition the plant and measurement noise are in some weighted ball of r sup n xl sub 2 finite horizon and infinite horizon cases are considered necessary and sufficient conditions are presented for the existence of estimators both filters and smoothers that achieve a prescribed performance bound and algorithms that result in performance within the bounds are developed in case of smoothers the optimal smoother is also presented the approach uses basic quadratic optimization theory in a time domain setting as a consequence of which both linear time varying and time invariant systems can be considered with equal ease in the smoothing problem for linear time varying systems one considers only the finite horizon case

a least squares algorithm for multipath time delay estimation we consider the problem of estimating the arrival times of overlapping ocean acoustic signals from a noisy received waveform that consists of attenuated and delayed replicas of a known transient signal we assume that the transmitted signal and the number of paths in the multipath environment are known and develop an algorithm that gives least squares ls estimates of the amplitude and time delay of each path direct computation of the ls estimates would involve minimization of a highly oscillatory error function by allowing the amplitudes to be complex valued a much smoother error function that is easier to minimize using gradient based techniques is obtained using this property and the knowledge derived from the data of the spacing between adjacent minima in the actual ls error function an efficient algorithm is devised the algorithm is a function of a data dependent parameter and we give rules for choosing this parameter the algorithm is demonstrated on a broad band signal using simulated data the proposed method is shown to achieve the cramer rao lower bound over a wide range of snr s comparisons are made with alternating projection ap and estimate maximize em algorithms

brief paper minimax state estimation for linear discrete time differential algebraic equations this paper presents a state estimation approach for an uncertain linear equation with a non invertible operator in hilbert space the approach addresses linear equations with uncertain deterministic input and noise in the measurements which belong to a given convex closed bounded set a new notion of a minimax observable subspace is introduced by means of the presented approach new equations describing the dynamics of a minimax recursive estimator for discrete time non causal differential algebraic equations daes are presented for the case of regular daes it is proved that the estimator s equation coincides with the equation describing the seminal kalman filter the properties of the estimator are illustrated by a numerical example

optimal unbiased filtering via linear matrix inequalities abstract solutions to the optimal h and l2 l unbiased reduced order filtering problems are obtained in terms of linear matrix inequalities lmis the order of the optimal filter is equal to the number of measurements both continuous and discrete time results are presented an explicit parametrization of all optimal unbiased filters is provided in terms of a free contractive matrix

zeros of spectral factors the geometry of splitting subspaces and the algebraic riccati inequality in this paper it is shown how the zero dynamics of not necessarily square spectral factors relate to the splitting subspace geometry of stationary stochastic models and to the corresponding algebraic riccati inequality the notion of output induced subspace of a minimal markovian splitting subspace which is the stochastic analogue of the supremal output nulling subspace in geometric control theory is introduced through this concept the analysis can be made coordinate free and straightforward geometric methods can be applied it is shown how the zero structure of the family of spectral factors relates to the geometric structure of the family of minimal markovian splitting subspaces in the sense that the relationship between the zeros of different spectral factors is reflected in the partial ordering of minimal splitting subspaces finally the well known characterization of the solutions of the algebraic riccati equation is generalized in terms of lagrangian subspaces invariant under the corresponding hamiltonian to the larger solution set of the algebraic riccati inequality

exponentially converging nystro spl uml m s methods for systems of singular integral equations with applications to open closed strip or slot loaded 2 d structures this paper concerns the fast highly accurate and exponentially convergent solution of three sets of integral equations pertaining to two dimensional generalized microstrip or microslot structures the analysis relies on nystroumlm s method with due regard to all singular integrals and slowly converging series that appear in the kernels the sophisticated treatment and efficient computation of such series and integrals is of paramount importance entailing the use of advanced techniques as a result of our specialized treatment the discretization procedures developed herein a fully account for both the singular nature of the kernels and the singularities of the solution at the edges b obviate the need for taking inner products with testing functions c appear to converge exponentially versus matrix size and d enable expressing all matrix elements via single finite sums detailed numerical examples and case studies illustrate the simplicity flexibility and remarkable efficiency of the algorithms

h sliding mode control for uncertain neutral type stochastic systems with markovian jumping parameters this paper is devoted to the investigation of h sliding mode control smc for uncertain neutral stochastic systems with markovian jumping parameters and time varying delays a sliding surface functional is firstly constructed then the sliding mode control law is designed to guarantee the reachability of the sliding surface in a finite time interval the sufficient conditions for asymptotically stochastic stability of sliding mode dynamics with a given disturbance attenuation level are presented in terms of linear matrix inequalities lmis finally an example is provided to illustrate the efficiency of the proposed method

some remarks on stability of stochastic singular systems with state dependent noise this paper discusses the stability for stochastic singular systems with state dependent noise in both continuous time and discrete time cases firstly the condition for the existence and uniqueness of the solution to stochastic singular systems is given based on this condition the stochastic ito singular system is transformed into a deterministic standard singular system by means of h representation method secondly new sufficient conditions for the stability of systems considered are derived in terms of strict linear matrix inequalities finally an example is given to illustrate the effectiveness of the obtained theoretical results

h sub spl infin filtering for singular systems this note considers the h sub spl infin filtering problem for linear continuous singular systems the purpose is the design of a linear filter such that the resulting error system is regular impulse free and stable while the closed loop transfer function from the disturbance to the filtering error output satisfies a prescribed h sub spl infin norm bound constraint without decomposing the original system matrices a necessary and sufficient condition for the solvability of this problem is obtained in terms of a set of linear matrix inequalities lmis when these lmis are feasible an explicit expression of a desired filter is given finally an illustrative example is presented to demonstrate the applicability of the proposed approach

on optimal e to e filtering abstract in this paper we consider the problem of finding a filter that minimizes the worst case magnitude l of the estimation error in the case of linear time invariant systems subjected to unknown but magnitude bounded l inputs these inputs consist of process and observation noise as well as initial conditions also the optimization problem is considered over an infinite time horizon taking a model matching approach suboptimal solutions are presented that stem from the resulting l induced norm minimization problem

scattering of arbitrarily polarized plane waves obliquely incident on infinite slots or strips in a planar stratified medium an exact analysis of three dimensional scattering by a slot or by a strip right on an interface between two adjacent layers of a planar stratified isotropic medium is presented the most general case of arbitrarily polarized obliquely incident plane waves is considered the formulation is based on systems of singular integral integrodifferential equations sie side these systems are discretized with the help of two independent algorithms developed by tsalamengas see ibid vol 46 p 1560 70 1998 filling up the matrix elements involves rapidly convergent spectral integrals the expression of the far radiated field is derived and numerical results are presented for several cases

new perspectives for maximum likelihood time delay estimation this paper introduces a new realization for maximum likelihood time delay estimation tde that illuminates the relationships between maximum likelihood tde and other methods we obtain the result by deriving the likelihood function using a fundamental method that appears to be new to the field of array processing this method is a natural complement to the generalized karhunen loeve expansion

exact maximum likelihood time delay estimation for short observation intervals an exact solution is presented to the problem of maximum likelihood time delay estimation for a gaussian source signal observed at two different locations in the presence of additive spatially uncorrelated gaussian white noise the solution is valid for arbitrarily small observation intervals that is the assumption t tau sub c mod d mod made in the derivation of the conventional asymptotic maximum likelihood aml time delay estimator where tau sub c is the correlation time of the various random processes involved and d is the differential time delay is relaxed the resulting exact maximum likelihood eml instrumentation is shown to consist of a finite time delay and sum beamformer followed by a quadratic postprocessor based on the eigenvalues and eigenfunctions of a one dimensional integral equation with nonconstant weight the solution of this integral equation is obtained for the case of stationary signals with rational power spectral densities finally the performance of the eml and aml estimators is compared by means of computer simulations

robust h infinity filtering for a class of non linear systems with state delay and parameter uncertainty this paper deals with the problem of robust h infinity filtering for a class of state delayed non linear systems with normbounded parameter uncertainty appearing in all the matrices of the linear part of the system model the non linearities are assumed to satisfy the global lipschitz conditions and appear in both the state and measured output equations attention is focused on the design of a non linear filter which ensures both the robust stability and a prescribed h infinity performance of the filtering error dynamics for all admissible uncertainties a sufficient condition for the existence of such a filter is given in terms of a linear matrix inequality lmi when this lmi is feasible the expression of a desired h infinity filter is also presented a numerical example is provided to demonstrate the applicability of the proposed approach

te scattering by conducting strips right on the planar interface of a three layered medium combining the fourier transform with powerful singular integral equation methods the authors investigate the scattering properties of a variety of two dimensional three layered planar structures loaded by a strip or a couple of coplanar strips right on an interface the primary excitation is the lowest order incident tm to strip axis surface wave mode or an incident e polarized plane wave in the practical case where the entire space is magnetically homogeneous the kernel of the integral equations is most conveniently decomposed into a singular closed form term added to an exponentially convergent inverse fourier integral an efficient accurate and stable numerical code is obtained and used to determine the strip induced current densities as well as any quantity of practical interest plotted results reveal that by a proper choice of certain geometrical parameters the structures may become very efficient radiators which can be designed to exhibit either very wideband and high directivity or considerable frequency scanning

discrete time h algebraic riccati equation and parametrization of all h filters this paper is concerned with the algebraic riccati equations ares related to the h filtering problem a necessary and sufficient condition for the h problem to be solvable is that the h are has a positive semidefinite stabilizing solution with an additional condition that a certain matrix is positive definite it is shown that such a stabilizing solution is a monotonically non increasing convex function of the prescribed h norm bound this property of the h are is very important for the analysis of the performance of the h filter in this paper the size of the set of all h filters is considered on the basis of the monotonicity of the above riccati solution it turns out that under a certain condition the degree of freedom of the h filter reduces a1 the optimal h norm bound these results provide a guideline for selecting the value of some numerical examples are included