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

stability and stabilization of t s fuzzy systems with time varying delays via augmented lyapunov krasovskii functionals this paper is concerned with the problem of stability and stabilization for takagi sugeno t s fuzzy systems with time varying delays by constructing a suitable lyapunov krasovskii functional sufficient conditions for ensuring the asymptotic stability and stabilization of the concerned fuzzy systems have been derived within the framework of linear matrix inequalities lmis the advantage and effectiveness of the proposed criteria will be shown through the comparison of maximum delay bounds with some results obtained by recently published papers via four numerical examples

norm constrained capon beamforming using multirank signal models with kalman filter implementation the performance of the capon beamforming is known to degrade dramatically in the presence of model mismatches especially when the desired signal is present in the training data to improve the robustness the diagonal loading technique was introduced however the major drawback is the selection of the diagonal loading level which is related to the unknown signal powers another way to alleviate performance degradation is to use a more accurate signal model of the array response in this paper a norm constrained capon beamforming using multirank signal models is proposed based on the pseudo observation method the quadratic constraints can be easily constructed the problem is solved by a nonlinear kalman filter which can be implemented on line the simulation results show that the design of the norm constraint value is less sensitive to the signal powers small angle mismatches and number of sensors with a standard linear array further it is shown that the use of a multirank signal model and kalman filter technique result in less self cancellation and performance degradation than that of the rank 1 signal model and the estimation of sample matrix

h_ infty stabilization for polynomial fuzzy time delay system a sum of squares approach the h infty stabilization problem for polynomial fuzzy time delay system pftds is investigated in this paper first a polynomial fuzzy controller is proposed to stabilize the pftds based on euler s homogeneity relation homogeneous polynomial lyapunov krasovskii functional and the developed polynomial slack variable matrices a novel stabilization condition without the assumption in common use is presented in terms of sum of squares sos in order to reduce the conservative and implementation cost the property of membership function and the right hand side technique are adopted also two relaxed h infty stabilization conditions for pftds which may or may not share the same fuzzy rules are proposed to illustrate the feasibility and merit of the proposed result three examples are provided in the first example a well known takagi sugeno fuzzy time delay system is demonstrated to show that the proposed sos based methods can provide a longer allowable delay time than do some existing linear matrix inequality based methods the second and third examples show the validity and feasibility of the proposed results for pftds with the same or fewer rule numbers of the polynomial fuzzy controller

decentralized techniques for the analysis and control of takagi sugeno fuzzy systems this paper discusses decentralized parallel distributed compensator design for takagi sugeno fuzzy systems the fuzzy system is viewed as an interconnection of subsystems some of which are strongly connected while others being weakly connected the necessary theory is developed so that one can associate this fuzzy system with another one in a higher dimensional space the so called expanded space design decentralized parallel distributed compensators in the expanded space then contract the solution for implementation on the original fuzzy system in this respect connective stability of the open loop and closed loop of the interconnected system is analyzed via the concepts of vector lyapunov functions and m matrices different lyapunov functions generate different results for the discrete time fuzzy system quadratic lyapunov generating the superior of the two following a similar approach stabilization of the closed loop fuzzy system using local parallel distributed compensators is investigated

doubly constrained robust capon beamformer the standard capon beamformer scb is known to have better resolution and much better interference rejection capability than the standard data independent beamformer when the array steering vector is accurately known however the major problem of the scb is that it lacks robustness in the presence of array steering vector errors in this paper we will first provide a complete analysis of a norm constrained capon beamforming nccb approach which uses a norm constraint on the weight vector to improve the robustness against array steering vector errors and noise our analysis of nccb is thorough and sheds more light on the choice of the norm constraint than what was commonly known we also provide a natural extension of the scb which has been obtained via covariance matrix fitting to the case of uncertain steering vectors by enforcing a double constraint on the array steering vector viz a constant norm constraint and a spherical uncertainty set constraint which we refer to as the doubly constrained robust capon beamformer dcrcb nccb and dcrcb can both be efficiently computed at a comparable cost with that of the scb performance comparisons of nccb dcrcb and several other adaptive beamformers via a number of numerical examples are also presented

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

stabilizing controller design for uncertain nonlinear systems using fuzzy models a lyapunov based stabilizing control design method for uncertain nonlinear dynamical systems using fuzzy models is proposed the controller is constructed using a design model of the dynamical process to be controlled the design model is obtained from the truth model using a fuzzy modeling approach the truth model represents a detailed description of the process dynamics the truth model is used in a simulation experiment to evaluate the performance of the controller design a method for generating local models that constitute the design model is proposed sufficient conditions for stability and stabilizability of fuzzy models using fuzzy state feedback controllers are given the results obtained are illustrated with a numerical example involving a four dimensional nonlinear model of a stick balancer

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

delay dependent robust stability criteria for uncertain systems with interval time varying delay this paper proposes an approach for the robust stability of uncertain systems with interval time varying delay the key features of the approach include the introduction of uncorrelated augmented matrix items into the lyapunov functional and the use of a tighter bounding technology unlike existing methodologies the proposed approach involves neither free weighting matrices nor any model transformation it can however lead to much less conservative stability criteria than the existing ones for the systems under consideration numerical examples show that the proposed criteria improve the existing results significantly with much less computational effort

some relations between extended and unscented kalman filters the unscented kalman filter ukf has become a popular alternative to the extended kalman filter ekf during the last decade ukf propagates the so called sigma points by function evaluations using the unscented transformation ut and this is at first glance very different from the standard ekf algorithm which is based on a linearized model the claimed advantages with ukf are that it propagates the first two moments of the posterior distribution and that it does not require gradients of the system model we point out several less known links between ekf and ukf in terms of two conceptually different implementations of the kalman filter the standard one based on the discrete riccati equation and one based on a formula on conditional expectations that does not involve an explicit riccati equation first it is shown that the sigma point function evaluations can be used in the classical ekf rather than an explicitly linearized model second a less cited version of the ekf based on a second order taylor expansion is shown to be quite closely related to ukf the different algorithms and results are illustrated with examples inspired by core observation models in target tracking and sensor network applications

optimal error estimates of the direct discontinuous galerkin method for convection diffusion equations abstract in this paper we present the optimal l2 error estimate ofo hk 1 for polynomial elements of degree k of the semidiscrete direct discontinuous galerkin method for convection diffusion equations the main technical difficulty lies in the control of the inter element jump terms which arise because of the convection and the discontinuous nature of numerical solutions the main idea is to use some global projections satisfying interface conditions dictated by the choice of numerical fluxes so that trouble terms at the cell interfaces are eliminated or controlled in multi dimensional case the orders of k 1 hinge on a superconvergence estimate when tensor product polynomials of degree k are used on cartesian grids a collection of projection errors in both oneand multi dimensional cases is established

an approach to fuzzy control of nonlinear systems stability and design issues presents a design methodology for stabilization of a class of nonlinear systems first the authors represent a nonlinear plant with a takagi sugeno fuzzy model then a model based fuzzy controller design utilizing the concept of the so called parallel distributed compensation is employed the main idea of the controller design is to derive each control rule so as to compensate each rule of a fuzzy system the design procedure is conceptually simple and natural moreover the stability analysis and control design problems can be reduced to linear matrix inequality lmi problems therefore they can be solved efficiently in practice by convex programming techniques for lmis the design methodology is illustrated by application to the problem of balancing and swing up of an inverted pendulum on a cart

robust implicit direct discontinuous galerkin method for simulating the compressible turbulent flows this paper proposes a robust and accurate implicit direct discontinuous galerkin ddg method for simulating laminar and turbulent flows the reynolds averaged navier stokes rans equations couple

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 further studies on lmi based relaxed stabilization conditions for nonlinear systems in takagi sugeno s form this paper further studies stabilization of nonlinear systems represented by a takagi sugeno t s discrete fuzzy model by extending a nonquadratic lyapunov function and applying a nonparallel distributed compensation non pdc law a new stabilization conclusion is presented that is a generalization of some previous results in the literature the new conclusion under a special situation is also suitable for a pdc law which presents to be more relaxed than some existing results an example is provided to demonstrate the effectiveness of the new conclusions

a direct discontinuous galerkin method for the compressible navierstokes equations on arbitrary grids a direct discontinuous galerkin ddg method is developed for solving the compressible navierstokes equations on arbitrary grids in the framework of dg methods the ddg method originally introduced for scalar diffusion problems on structured grids is extended to discretize viscous and heat fluxes in the navierstokes equations two approaches of implementing the ddg method to compute numerical diffusive fluxes for the navierstokes equations are presented one is based on the conservative variables and the other is based on the primitive variables the importance of the characteristic cell size used in the ddg formulation on unstructured grids is examined the numerical fluxes on the boundary by the ddg method are discussed a number of test cases are presented to assess the performance of the ddg method for solving the compressible navierstokes equations based on our numerical results we observe that ddg method can achieve the designed order of accuracy and is able to deliver the same accuracy as the widely used br2 method at a significantly reduced cost clearly demonstrating that the ddg method provides an attractive alternative for solving the compressible navierstokes equations on arbitrary grids owning to its simplicity in implementation and its efficiency in computational cost

mixed h sub 2 h sub spl infin fuzzy output feedback control design for nonlinear dynamic systems an lmi approach this study introduces a mixed h sub 2 h sub spl infin fuzzy output feedback control design method for nonlinear systems with guaranteed control performance first the takagi sugeno fuzzy model is employed to approximate a nonlinear system next based on the fuzzy model a fuzzy observer based mixed h sub 2 h sub spl infin controller is developed to achieve the suboptimal h sub 2 control performance with a desired h sub spl infin disturbance rejection constraint a robust stabilization technique is also proposed to override the effect of approximation error in the fuzzy approximation procedure by the proposed decoupling technique and two stage procedure the outcome of the fuzzy observer based mixed h sub 2 h sub spl infin control problem is parametrized in terms of the two eigenvalue problems evps one for observer and the other for controller the evps can be solved very efficiently using the linear matrix inequality lmi optimization techniques a simulation example is given to illustrate the design procedures and performances of the proposed method

new approaches to h controller designs based on fuzzy observers for t s fuzzy systems via lmi the problems of relaxed quadratic stability conditions fuzzy observer designs and h controller designs for t s fuzzy systems have been studied first new stability conditions are obtained by relaxing the stability conditions derived in previous papers secondly new fuzzy observers based on the relaxed stability conditions for the t s fuzzy systems have been proposed thirdly two sufficient lmi conditions which guarantee the existence of the h controllers based on fuzzy observers for the t s fuzzy systems have been proposed the conditions are not only simple but also consider the interactions among the fuzzy subsystems finally by some examples using the lmi technique we show that the regulators the fuzzy observers and the h controller designs based on new observers for the t s fuzzy systems are very practical and efficient

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

adaptive beamforming using the constrained kalman filter from the viewpoint of achieving rapid convergence application of a kalman filter to an adaptive array is considered compared with the frost s 1972 constrained least mean square algorithm the constrained kalman algorithm for adaptive beamforming is proposed to overcome the problem of signal distortion along the look direction which occurs in the unconstrained kalman beamformer of baird 1974 a constraint on the array response along the look direction is added to the measurement equation of the kalman filter the weight vector of the constrained kalman beamformer is derived and shown to converge to that of the minimum variance distortionless response beamformer the convergence rate of the proposed algorithm is also analyzed compared to baird s algorithm and the sidelobe canceller with one step kalman predictor simulation results show the effectiveness of the proposed algorithm

regular paper the takagi sugeno fuzzy controllers using the simplified linear control rules are nonlinear variable gain controllers takagi sugeno ts for short fuzzy controllers have been used and treated as black box controllers and there exists no explicit structure of any ts fuzzy controller in the literature in this paper we investigate the analytical structure of the ts fuzzy controllers that use our newly introduced simplified ts control rule scheme our scheme requires that all the rule consequent employ a common linear function and be proportional to one another the scheme drastically reduces the number of adjustable parameters required by the original ts rule scheme product fuzzy logic and was employed in the rule antecedents we theoretically proved that the ts controllers using the simplified rule scheme were nonlinear variable gain controllers the proportionality of the rule consequent parameterized the gain variation characteristics as special cases the ts controllers with three or two input variables and the simplified linear rule consequent were nonlinear variable gain pid pi or pd controllers as an illustration we mathematically analyzed the nonlinear variable gain pi controllers and revealed that the gain variation empowered the controllers to outperform their linear counterparts stability of the nonlinear pi control systems was also addressed a practical example is given to show how to achieve the desired characteristics of the gain variation by properly designing the simplified rules

a ghost cell immersed boundary method for flow in complex geometry an efficient ghost cell immersed boundary method gcibm for simulating turbulent flows in complex geometries is presented a boundary condition is enforced through a ghost cell method the reconstruction procedure allows systematic development of numerical schemes for treating the immersed boundary while preserving the overall second order accuracy of the base solver both dirichlet and neumann boundary conditions can be treated the current ghost cell treatment is both suitable for staggered and non staggered cartesian grids the accuracy of the current method is validated using flow past a circular cylinder and large eddy simulation of turbulent flow over a wavy surface numerical results are compared with experimental data and boundary fitted grid results the method is further extended to an existing ocean model mitgcm to simulate geophysical flow over a three dimensional bump the method is easily implemented as evidenced by our use of several existing codes

high order discontinuous galerkin method for computation of turbulent flows this paper presents a high order discontinuous galerkin method for computation of compressible turbulent flows in three space dimensions a modified spalart and allmaras turbulence model is implemented and discretized to the same order of accuracy as that for the reynolds averaged navier stokes equations the creation of curvilinear meshes for arbitrary three dimensional configurations is achieved through the aid of a computational analysis programming interface which enables direct communications with the computer aided design module to determine the true positions of surface quadrature points for high order geometric representations a modified linear elasticity approach is used sequentially and is of crucial importance for reshaping the interior mesh to allow high aspect ratio curved elements in turbulent boundary layers requirements of the mesh parameters including the wall spacing and viscous stretching factor are studied and it is concluded that for attached turbulent flows the conventional s

delay dependent robust stabilization of uncertain state delayed systems this paper concerns a problem of robust stabilization of uncertain state delayed systems a new delay dependent stabilization condition using a memoryless controller is formulated in terms of matrix inequalities an algorithm involving convex optimization is proposed to design a controller guaranteeing a suboptimal maximal delay such that the system can be stabilized for all admissible uncertainties

sampled data filtering of takagi sugeno fuzzy neural networks with interval time varying delays abstract this paper is concerned with sample data filtering of t s fuzzy neural networks with interval time varying delays which is formed by a fuzzy plant with time delay and a sampled data fuzzy controller connected in a closed loop a takagi sugeno t s fuzzy model is adopted for the neural networks and the sampled data fuzzy controller is designed for a t s fuzzy system to develop the guaranteed cost control a new stability condition of the closed loop system is guaranteed in the continuous time lyapunov sense and its sufficient conditions are formulated in terms of linear matrix inequalities by using a descriptor representation the sampled data fuzzy control system with time delay can be reduced to ease the stability analysis which effectively leads to a smaller number of lmi stability conditions information of the membership functions of both the fuzzy plant model and fuzzy controller are considered which allows arbitrary matrices to be introduced to ease the satisfaction of the stability conditions by a newly proposed inequality bounding technique the fuzzy sampled data filtering performance analysis is carried out such that the resultant neural networks is asymptotically stable numerical example and simulation result are given to illustrate the usefulness and effectiveness of the proposed theoretical results

a robust null space method for linear equality constrained state estimation we present a robust null space method for linear equality constrained state space estimation exploiting a degeneracy in the estimator statistics an orthogonal factorization is used to decompose the problem into stochastic and deterministic components which are then solved separately the resulting dimension reduction algorithm has enhanced numerical stability solves the constrained problem completely and can reduce computational load by reducing the problem size the new method addresses deficiencies in commonly used pseudo observation or projection methods which either do not solve the constrained problem completely or have unstable numerical implementations due in part to the degeneracy in the estimator statistics we present a numerical example demonstrating the effectiveness of the new method compared to other current methods

on kalman filtering with nonlinear equality constraints the state space description of some physical systems possess nonlinear equality constraints between some state variables in this paper we consider the problem of applying a kalman filter type estimator in the presence of such constraints we categorize previous approaches into pseudo observation and projection methods and identify two types of constraints those that act on the entire distribution and those that act on the mean of the distribution we argue that the pseudo observation approach enforces neither type of constraint and that the projection method enforces the first type of constraint only we propose a new method that utilizes the projection method twice once to constrain the entire distribution and once to constrain the statistics of the distribution we illustrate these algorithms in a tracking system that uses unit quaternions to encode orientation

eigenvalue beamforming using a multirank mvdr beamformer and subspace selection we derive eigenvalue beamformers to resolve an unknown signal of interest whose spatial signature lies in a known subspace but whose orientation in that subspace is otherwise unknown the unknown orientation may be fixed in which case the signal covariance is rank 1 or it may be random in which case the signal covariance is multirank we present a systematic treatment of such signal models and explain their relevance for modeling signal uncertainties we then present a multirank generalization of the mvdr beamformer the idea is to minimize the power at the output of a matrix beamformer while enforcing a data dependent distortionless constraint in the signal subspace which we design based on the type of signal we wish to resolve we show that the eigenvalues of an error covariance matrix are fundamental for resolving signals of interest signals with rank 1 covariances are resolved by the largest eigenvalues of the error covariance while signals with multirank covariances are resolved by the smallest eigenvalues thus the beamformers we design are eigenvalue beamformers which extract signal information from eigen modes of an error covariance we address the tradeoff between angular resolution of eigenvalue beamformers and the fraction of the signal power they capture

robust adaptive beamforming for general rank signal models the performance of adaptive beamforming methods is known to degrade severely in the presence of even small mismatches between the actual and presumed array responses to the desired signal such mismatches may frequently occur in practical situations because of violation of underlying assumptions on the environment sources or sensor array this is especially true when the desired signal components are present in the beamformer training data snapshots because in this case the adaptive array performance is very sensitive to array and model imperfections the similar phenomenon of performance degradation can occur even when the array response to the desired signal is known exactly but the training sample size is small we propose a new powerful approach to robust adaptive beamforming in the presence of unknown arbitrary type mismatches of the desired signal array response our approach is developed for the most general case of an arbitrary dimension of the desired signal subspace and is applicable to both the rank one point source and higher rank scattered source fluctuating wavefront desired signal models the proposed robust adaptive beamformers are based on explicit modeling of uncertainties in the desired signal array response and data covariance matrix as well as worst case performance optimization simple closed form solutions to the considered robust adaptive beamforming problems are derived our new beamformers have a computational complexity comparable with that of the traditional adaptive beamforming algorithms while at the same time offer a significantly improved robustness and faster convergence rates

multichannel post filtering in nonstationary noise environments in this paper we present a multichannel post filtering approach for minimizing the log spectral amplitude distortion in nonstationary noise environments the beamformer is realistically assumed to have a steering error a blocking matrix that is unable to block all of the desired signal components and a noise canceller that is adapted to the pseudo stationary noise but not modified during transient interferences a mild assumption is made that a desired signal component is stronger at the beamformer output than at any reference noise signal and a noise component is strongest at one of the reference signals the ratio between the transient power at the beamformer output and the transient power at the reference noise signals is used to indicate whether such a transient is desired or interfering based on a gaussian statistical model and combined with an appropriate spectral enhancement technique we derive estimators for the signal presence probability the noise power spectral density and the clean signal the proposed method is tested in various nonstationary noise environments compared with single channel post filtering a significantly reduced level of nonstationary noise is achieved without further distorting the desired signal components

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

h_ infty filter design for nonlinear systems with time delay through t s fuzzy model approach this paper is concerned with the hinfin filter design for nonlinear systems with time varying delay via takagi sugeno fuzzy model approach delay dependent design method is proposed in terms of linear matrix inequalities lmis which forms the main contribution of this paper the main technique used is the free weighting matrix method combined with a matrix decoupling approach the results for rate independent case delay independent case and delay free case are also given as easy corollaries an illustrative example is given to show the effectiveness of the present method

new delay dependent stability criteria for t s fuzzy systems with time varying delay this paper is concerned with the stability problem of uncertain t s fuzzy systems with time varying delay by employing a further improved free weighting matrix approach by taking the relationship among the time varying delay its upper bound and their difference into account some less conservative lmi based delay dependent stability criteria are obtained without ignoring any useful terms in the derivative of lyapunov krasovskii functional finally two numerical examples are given to demonstrate the effectiveness and the merits of the proposed methods

a recursive least squares implementation for lcmp beamforming under quadratic constraint quadratic constraints on the weight vector of an adaptive linearly constrained minimum power lcmp beamformer can improve robustness to pointing errors and to random perturbations in sensor parameters we propose a technique for implementing a quadratic inequality constraint with recursive least squares rls updating a variable diagonal loading term is added at each step where the amount of loading has a closed form solution simulations under different scenarios demonstrate that this algorithm has better interference suppression than both the rls beamformer with no quadratic constraint and the rls beamformer using the scaled projection technique as well as faster convergence than lms beamformers

further improvement of free weighting matrices technique for systems with time varying delay a novel method is proposed in this note for stability analysis of systems with a time varying delay appropriate lyapunov functional and augmented lyapunov functional are introduced to establish some improved delay dependent stability criteria less conservative results are obtained by considering the additional useful terms which are ignored in previous methods when estimating the upper bound of the derivative of lyapunov functionals and introducing the new free weighting matrices the resulting criteria are extended to the stability analysis for uncertain systems with time varying structured uncertainties and polytopic type uncertainties numerical examples are given to demonstrate the effectiveness and the benefits of the proposed method

technical communique observer based h fuzzy control design for t s fuzzy systems with state delays this paper is concerned with the problem of observer based h fuzzy control design for takagi sugeno t s fuzzy systems with time delay the main contribution is that an effective matrix decoupling technique is developed to derive a single step lmi condition for observer based h control design this overcomes the drawback of two step lmi approach in the literature when restricted to delay free fuzzy systems the present result is shown less conservative than existing ones an illustrative example is given to show the effectiveness of our results

a reconstructed discontinuous galerkin method for the compressible navier stokes equations on arbitrary grids a reconstruction based discontinuous galerkin rdg method is presented for the solution of the compressible navier stokes equations on arbitrary grids the rdg method originally developed for the compressible euler equations is extended to discretize viscous and heat fluxes in the navier stokes equations using a so called inter cell reconstruction where a smooth solution is locally reconstructed using a least squares method from the underlying discontinuous dg solution similar to the recovery based dg rdg methods this reconstructed dg method eliminates the introduction of ad hoc penalty or coupling terms commonly found in traditional dg methods unlike rdg methods this rdg method does not need to judiciously choose a proper form of a recovered polynomial thus is simple flexible and robust and can be used on arbitrary grids the developed rdg method is used to compute a variety of flow problems on arbitrary meshes to demonstrate its accuracy efficiency robustness and versatility the numerical results indicate that this rdg method is able to deliver the same accuracy as the well known bassi rebay ii scheme at a half of its computing costs for the discretization of the viscous fluxes in the navier stokes equations clearly demonstrating its superior performance over the existing dg methods for solving the compressible navier stokes equations

new delay dependent stabilization conditions of t s fuzzy systems with constant delay this paper focuses on the problem of robust control for takagi sugeno t s fuzzy systems with time delay the delay dependent stability analysis and controller synthesis have been addressed the free weighting matrix method has been used for stability analysis and controller synthesis new and less conservative delay dependent stability conditions are proposed in terms of linear matrix inequalities lmi finally some examples are given to illustrate the effectiveness of the proposed approaches

a riccati equation approach to the stabilization of uncertain linear systems this paper presents a method for designing a feedback control law to stabilize a class of uncertain linear systems the systems under consideration contain uncertain parameters whose values are known only to within a given compact bounding set furthermore these uncertain parameters may be time varying the method used to establish asymptotic stability of the closed loop system obtained when the feedback control is applied involves the use of a quadratic lyapunov function the main contribution of this paper involves the development of a computationally feasible algorithm for the construction of a suitable quadratic lyapunov function once the lyapunov function has been obtained it is used to construct the stabilizing feedback control law the fundamental idea behind the algorithm presented involves constructing an upper bound for the lyapunov derivative corresponding to the closed loop system this upper bound is a quadratic form by using this upper bounding procedure a suitable lyapunov function can be found by solving a certain matrix riccati equation another major contribution of this paper is the identification of classes of systems for which the success of the algorithm is both necessary and sufficient for the existence of a suitable quadratic lyapunov function

efficient subspace based estimator for localization of multiple incoherently distributed sources in this paper a new subspace based algorithm for parametric estimation of angular parameters of multiple incoherently distributed sources is proposed this approach consists of using the subspace principle without any eigendecomposition of the covariance matrix so that it does not require the knowledge of the effective dimension of the pseudosignal subspace and therefore the main difficulty of the existing subspace estimators can be avoided the proposed idea relies on the use of the property of the inverse of the covariance matrix to exploit approximately the orthogonality property between column vectors of the noise free covariance matrix and the sample pseudonoise subspace the resulting estimator can be considered as a generalization of the pisarenko s extended version of capon s estimator from the case of point sources to the case of incoherently distributed sources theoretical expressions are derived for the variance and the bias of the proposed estimator due to finite sample effect compared with other known methods with comparable complexity the proposed algorithm exhibits a better estimation performance especially for close source separation for large angular spread and for low signal to noise ratio

parametric localization of distributed sources most array processing algorithms are based on the assumption that the signals are generated by point sources this is a mathematical constraint that is not satisfied in many applications in this paper we consider situations where the sources are distributed in space with a parametric angular cross correlation kernel we propose an algorithm that estimates the parameters of this model using a generalization of the music algorithm the method involves maximizing a cost function that depends on a matrix array manifold and the noise eigenvectors we study two particular cases coherent and incoherent spatial source distributions the spatial correlation function for a uniformly distributed signal is derived from this we find the array gain and show that in contrast to point sources it does not increase linearly with the number of sources we compare our method to the conventional point source music algorithm the simulation studies show that the new method outperforms the music algorithm by reducing the estimation bias and the standard deviation for scenarios with distributed sources it is also shown that the threshold signal to noise ratio required for resolving two closely spaced distributed sources is considerably smaller for the new method

the compact discontinuous galerkin cdg method for elliptic problems we present a compact discontinuous galerkin cdg method for an elliptic model problem the problem is first cast as a system of first order equations by introducing the gradient of the primal unknown or flux as an additional variable a standard discontinuous galerkin dg method is then applied to the resulting system of equations the numerical interelement fluxes are such that the equations for the additional variable can be eliminated at the element level thus resulting in a global system that involves only the original unknown variable the proposed method is closely related to the local discontinuous galerkin ldg method b cockburn and c w shu siam j numer anal 35 1998 pp 2440 2463 but unlike the ldg method the sparsity pattern of the cdg method involves only nearest neighbors also unlike the ldg method the cdg method works without stabilization for an arbitrary orientation of the element interfaces the computation of the numerical interface fluxes for the cdg method is slightly more involved than for the ldg method but this additional complication is clearly offset by increased compactness and flexibility compared to the br2 f bassi and s rebay j comput phys 131 1997 pp 267 279 and ip j douglas jr and t dupont in computing methods in applied sciences second internat sympos versailles 1975 lecture notes in phys 58 springer berlin 1976 pp 207 216 methods which are known to be compact the present method produces fewer nonzero elements in the matrix and is computationally more efficient