optimal design of constraint following control for fuzzy mechanical systems the control problem for a mechanical system to follow a constraint is formulated the uncertainty is considered in both the system dynamics and constraint it is bounded and the knowledge of the bound only lies within a fuzzy set we propose an adaptive robust control for the mechanical system for approximate constraint following both the mechanical system model and control scheme are deterministic and not if then heuristic rules based an optimal design problem using the fuzzy description of the uncertainty is proposed we prove that the global solution to the resulting optimization problem always exists and is unique under the control the performance of the mechanical system is both deterministically guaranteed and fuzzily optimized

continuous takagi sugeno s models reduction of the number of lmi conditions in various fuzzy control design technics fuzzy models of the takagi sugeno type enable representation of a wide class of nonlinear models conditions about their stabilization can be derived systematically usually these conditions are written as linear matrix inequality lmi problems in this paper we use a collection of properties concerning matrices to extend the area of solutions involving the feedback control laws we will work out with continuous fuzzy models and supply results about the stabilization the regulator problem and also hinfin control solutions based on a reduced number of decision variables implying a reduced number of lmi conditions are also proposed we show that a good tradeoff can been obtained

delay dependent decentralized h_ infty filtering for discrete time nonlinear interconnected systems with time varying delay based on the t s fuzzy model this paper is concerned with the problem of delay dependent h filter design for a class of discrete time nonlinear interconnected system with time varying delays via the takagi sugeno t s fuzzy model the t s fuzzy model consists of n time delay t s fuzzy subsystems and a decentralized h filter is designed for each subsystem based on the delay dependent piecewise lyapunov krasovskii functional ddplkf and with an improved free weighting matrix technique the delay dependent stability and a prescribed h performance index are guaranteed for the overall filtering error system a sufficient condition for the existence of such a filter is established by using linear matrix inequalities lmis that are numerically feasible two numerical examples are given to demonstrate the effectiveness and advantage of the proposed approach

a nash game approach to mixed h sub 2 h sub spl infin control the established theory of nonzero sum games is used to solve a mixed h sub 2 h sub spl infin control problem our idea is to use the two pay off functions associated with a two player nash game to represent the h sub 2 and h sub spl infin criteria separately we treat the state feedback problem and we find necessary and sufficient conditions for the existence of a solution both the finite and infinite time problems are considered in the infinite horizon case we present a full stability analysis the resulting controller is a constant state feedback law characterized by the solution to a pair of cross coupled riccati equations which may be solved using a standard numerical integration procedure we begin our development by considering strategy sets containing linear controllers only at the end of the paper we broaden the strategy sets to include a class of nonlinear controls it turns out that this extension has no effect on the necessary and sufficient conditions for the existence of a solution or on the nature of the controllers

lqg control with an h sup infinity performance bound a riccati equation approach an lqg linear quadratic gaussian control design problem involving a constraint on h sup infinity disturbance attenuation is considered the h sup infinity performance constraint is embedded within the optimization process by replacing the covariance lyapunov equation by a riccati equation whose solution leads to an upper bound on l sub 2 performance in contrast to the pair of separated riccati equations of standard lqg theory the h sup infinity constrained gains are given by a coupled system of three modified riccati equations the coupling illustrates the breakdown of the separation principle for the h sup infinity constrained problem both full and reduced order design problems are considered with an h sup infinity attenuation constraint involving both state and control variables an algorithm is developed for the full order design problem and illustrative numerical results are given

on mapping fracture networks onto continuum 1 discrete fracture network dfn and stochastic continuum sc are two common modeling approaches used for simulating fluid flow and solute transport in fractured media fracture continuum approaches combine the merits of each approach details of the fracture network are preserved and a computationally efficient grid is utilized for the solution of fluid flow by assigning a conductivity contrast between the grid cells representing the rock matrix and those representing fractures in this paper we propose a fracture continuum approach for mapping individual fractures onto a finite difference grid as conductivity fields we focus on several issues that are associated with this approach such as enhanced connectivity between fractures that would otherwise not be in connection in a dfn simulation and the influence of grid cell size to addresses these issues both dfn and the proposed approach are used to solve for fluid flow through two dimensional randomly generated fracture networks in a steady state single phase flow system the dfn flow solution is used as a metric to evaluate the robustness of the method in translating discrete fractures onto grid cell conductivities on four different regularly spaced grids 1 1 m 2 2 m 5 5 m and 10 10 m two correction factors are introduced to ensure equivalence between the total flow of the grid and the original fracture network the first is dependent on the fracture alignment with the grid and is set to account for the difference between the length of the flow path on the grid and that of the fracture the other correction is applied for areas in the grid with high fracture density and accounts for the artificial degree of connectivity that exists on the grid but not in the dfn fifteen different cases are studied to evaluate the effect of fracture statistics on the results of the proposed approach and by taking average results of 100 realizations in each case in a stochastic monte carlo framework the flow equation is solved for the dfn and total flow is obtained the flow is also solved separately for the four grid resolution levels and comparisons between the dfn and the grid total flows are made for the different cases and the different grid resolution levels the approach performed relatively well in all cases for the fine grid resolution but an overestimation of grid flow is observed in the coarse grid resolution especially for cases wherein the network connectivity is controlled by small fractures this overestimation shows minor variation from one realization to another within the same case this allowed us to develop an approach that depends on solving limited number of dfn simulations to obtain this overestimation factor results indicate that the proposed approach provides improvements over existing approaches and has a potential to provide a link between dfn and sc models

multiobjective boldmath ht hf control design an important question in feedback control design is how to achieve desired performance for dynamical systems subject to both model uncertainties and white noise for this purpose it is desirable to develop a systematic design technique that combines the good aspects of both cal h 2 lqg and cal h infty methods which provides the motivation for the development of multiobjective design framework in this paper encouraged by a time domain game approach for cal h 2 cal h infty control design two multiobjective control design problems are formulated and solved in the time domain results for both the finite time horizon and the infinite time horizon are presented it is shown that all the results can be obtained by solving the corresponding set of coupled riccati equations

stabilization of networked stochastic time delay fuzzy systems with data dropout this paper deals with the problem of stabilization for networked stochastic systems with transmitted data dropout the plant in the networked control system ncs under consideration is a discrete stochastic time delay nonlinear system represented by a takagi sugeno fuzzy model exponential stability criteria of the ncs are developed by using a common quadratic lyapunov function and a fuzzy lyapunov function respectively a stabilization controller with convergence rate constraint can be designed by solving a set of linear matrix inequalities that is numerically feasible with commercially available software three numerical examples are presented to demonstrate the effectiveness of the proposed methods

an algorithm for multistage dynamic networks with random arc capacities with an application to dynamic fleet management we consider the class of multistage dynamic networks with random arc capacities a framework that is well suited to model dynamic fleet management problems we propose a successive convex approximation approach that produces an approximation to the expected recourse function which captures the future effects of current decisions under uncertainty this method decomposes the network in each stage into tree subproblems whose expected recourse functions are easy to obtain we also compare this method with two alternative methods on a set of dynamic fleet management problems the numerical results show that this method is superior to the two alternative methods

h spl infin decentralized fuzzy model reference tracking control design for nonlinear interconnected systems in general due to the interactions among subsystems it is difficult to design an h sub spl infin decentralized controller for nonlinear interconnected systems the model reference tracking control problem of nonlinear interconnected systems is studied via h sub spl infin decentralized fuzzy control method first the nonlinear interconnected system is represented by an equivalent takagi sugeno type fuzzy model a state feedback decentralized fuzzy control scheme is developed to override the external disturbances such that the h spl infin model reference tracking performance is achieved furthermore the stability of the nonlinear interconnected systems is also guaranteed if states are not all available a decentralized fuzzy observer is proposed to estimate the states of each subsystem for decentralized control consequently a fuzzy observer based state feedback decentralized fuzzy controller is proposed to solve the h sub spl infin tracking control design problem for nonlinear interconnected systems the problem of h sub spl infin decentralized fuzzy tracking control design for nonlinear interconnected systems is characterized in terms of solving an eigenvalue problem evp the evp can be solved very efficiently using convex optimization techniques finally simulation examples are given to illustrate the tracking performance of the proposed methods

on delay dependent approach for robust stability and stabilization of t s fuzzy systems with constant delay and uncertainties this paper investigates robust stability analysis and stabilization of delay and uncertain systems approximated by a takagi sugeno t s fuzzy model an innovative approach is proposed to develop delay dependent stability criteria of the systems which makes use of less redundant information to construct lyapunov function employs an integral equation method to handle the cross product terms and alleviates the requirements of the bounding technique and model transformations that have been popularly adopted in many existing references this leads to significant improvement in the stability performance with far fewer unknown variables in the stability computation from the derived stability criteria a new memoryless state feedback control is further developed the controller gain and the maximum allowable delay bound of the closed loop control system can be obtained simultaneously by solving an optimization problem numerical examples are also given to demonstrate the theoretical results

fuzzy h_ infty filter design for a class of nonlinear discrete time systems with multiple time delays this paper studies the fuzzy hinfin filter design problem for signal estimation of nonlinear discrete time systems with multiple time delays and unknown bounded disturbances first the takagi sugeno t s fuzzy model is used to represent the state space model of nonlinear discrete time systems with time delays next we design a stable fuzzy hinfin filter based on the t s fuzzy model which guarantees asymptotic stability and a prescribed hinfin index for the filtering error system irrespective of the time delays and uncertain disturbances a sufficient condition for the existence of such a filter is established by using the linear matrix inequality lmi approach the proposed lmi problem can be efficiently solved with global convergence guarantee using convex optimization techniques such as the interior point algorithm simulation examples are provided to illustrate the design procedure of the present method

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

robust h infinity control in the presence of stochastic uncertainty this paper considers a robust h infinity state feedback control problem for linear uncertain systems with stochastic uncertainty the uncertainty class considered in the paper involves uncertain multiplicative white noise perturbations which satisfy a certain variance constraint a state feedback controller is presented which guarantees a prescribed level of disturbance attenuation for all admissible stochastic uncertainties

delay dependent stability analysis and controller synthesis for discrete time t s fuzzy systems with time delays based on a novel delay dependent piecewise lyapunov krasovskii functional dplkf this paper presents delay dependent stability analysis and synthesis methods for discrete time takagi sugeno t s fuzzy systems with time delays it is shown that the stability and stabilization with some required performance can be established for the closed loop control system if there exists a dplkf and that the dplkf and the corresponding controller can be obtained by solving a set of linear matrix inequalities lmis new algorithms have also been developed to obtain the maximum value of the allowable constant delay and the suboptimal performance upper bound an example is finally presented to demonstrate the efficiency and advantage of the proposed methods

multiobjective tracking control design of t s fuzzy systems in this study a multiobjective fuzzy control design method is introduced for nonlinear dynamic systems to guarantee the optimal h 2 and h reference tracking performance simultaneously first the takagi and sugeno t s fuzzy model is used to represent the nonlinear dynamic system then based on the t s fuzzy model multiobjective h 2 h tracking control design problem is formulated as a multiobjective problem mop to minimize the h 2 tracking error and h disturbance attenuation level for the fuzzy system at the same time since it is not easy to solve this mop directly an indirect method is proposed for the multiobjective h 2 h tracking control design finally in order to achieve the simultaneous optimization of the mop linear matrix inequality lmi based multiobjective evolution algorithm lmi based moea is developed based on non dominating sorting scheme to efficiently search the set of pareto optimal solutions for the mop from which designer can select one design according to his own preference further the multiobjective h 2 h fuzzy control design problem based on the weighted sum method is also solved as an alternative choice finally a simulation example of a robotic system is given to illustrate the design procedure and to confirm the robust and optimal tracking performance of the proposed method

h_ infty filter design for a class of networked control systems via t s fuzzy model approach this paper is concerned with h design for a class of networked control systems ncss with multiple state delays via the takagi sugeno t s fuzzy model the transfer delays and packet loss that are induced by the limited bandwidth of communication networks are considered the focus of this paper is on the analysis and design of a full order h filter such that the filtering error dynamics are stochastically stable and a prescribed h attenuation level is guaranteed sufficient conditions are established for the existence of the desired filter in terms of linear matrix inequalities lmis an example is given to illustrate the effectiveness and applicability of the proposed design method

robust filter for nonlinear stochastic partial differential systems in sensor signal processing fuzzy approach this study addresses a robust h filter design problem for nonlinear stochastic partial differential systems nspdss with random external disturbance and measurement noise in the spatiotemporal domain for nspdss a robust h filter design through a set of sensor measurements needs to solve a complex second order hamilton jacobi integral inequality hjii in order to simplify the design procedure a fuzzy stochastic partial differential system based on a fuzzy interpolation approach is proposed to approximate the nspds then a fuzzy stochastic spatial state space model is developed to represent the fuzzy stochastic partial differential system via the semidiscretization finite difference scheme and the kronecker product based on this model a robust h filter design is proposed to achieve the robust state estimation via solving linear matrix inequalities lmis instead of a second order hjii the proposed robust fuzzy h filter efficiently attenuates the effect of spatiotemporal external disturbances and measurement noise on the state estimation of nspdss from the area energy point of view finally a robust h state estimation example of heat transfer system is given to illustrate the design procedure and to confirm the h filtering performance of the proposed robust filter design method

on the connectivity of three dimensional fault networks natural fault networks involve a very broad range of fault lengths modeled in general by a power law length distribution n l al such a scaling law does not allow to define any a priori pertinent scale of observation for hydraulic field experiments in fractured media to investigate the relative effects of faults depending on their length we undertake in the spirit of percolation theory a theoretical and numerical study of the connectivity of three dimensional fault networks following power law length distributions we first establish the correct analytical expression of a percolation parameter p which describes the connectivity of the system the parameter p is found to be dependent on the third moment of the length distribution for fault planes it allows us to identify different regimes of connectivity depending on a the exponent of the fault length distribution the geometrical properties of the infinite cluster which partly control transport properties are also established at the percolation threshold for natural fault networks our theoretical analysis suggests that faults larger than a critical length scale may form a well connected network while smaller faults may be not connected on average this result which implies an increase of the connectivity with scale is consistent with scaling effects observed on permeability measurements

a correlated fracture network modeling and percolation properties 1 we present a model of fractures based on the idea that the elastic free energy due to the fracture density follows a boltzmann distribution the resulting expression for the spatial correlation in the displacement of fractures is used as an objective function in a simulated annealing algorithm to generate realizations of correlated fracture networks this approach determines the appropriate statistical distribution for the fractures e g length distribution rather than imposing them as is done conventionally the model consists of two families of parallel fractures which are perpendicular under isotropic conditions there also exists a positive correlation between the position of fractures and their lengths that is large fractures have their neighbors located at greater distance than small fractures finally we use the realizations of correlated fracture networks in the basic methodology of the percolation approach and investigate the model percolation properties in particular the scaling exponents of the connectivity are found to be different from the conventional uncorrelated values

a piecewise linear upper bound on the network recourse function we consider the optimal value of a pure minimum cost network flow problem as a function of supply demand and arc capacities we present a new piecewise linear upper bound on this function which is called the network recourse function the bound is compared to the standard madansky bound and is shown computationally to be a little weaker but much faster to find the amount of work is linear in the number of stochastic variables not exponential as is the case for the madansky bound therefore the reduction in work increases as the number of stochastic variables increases computational results are presented

time delay estimation in continuous linear time invariant systems the use of a time delay in modeling lti systems is quite common however attempts to estimate these time delays in continuous systems typically resorted to methods which increase the number of parameters in the system in contradiction to the use of time delay in the model to begin with we present here an attempt to estimate the time delays directly the algorithm we present is supported both by analysis and simulations with very encouraging results

the equal flow problem abstract this paper presents a new algorithm for the solution of a network problem with equal flow side constraints the solution technique is motivated by the desire to exploit the special structure of the side constraints and to maintain as much of the characteristics of pure network problems as possible the proposed algorithm makes use of lagrangean relaxation to obtain a lower bound and decomposition by right hand side allocation to obtain upper bounds the lagrangean dual serves not only to provide a lower bound used to assist in termination criteria for the upper bound but also allows an initial allocation of equal flows for the upper bound the algorithm has been tested on problems with up to 1500 nodes and 6000 arcs computational experience indicates that solutions whose objective function value is well within 1 of the optimum can be obtained in 1 65 of the mpsx time depending on the amount of imbalance inherent in the problem incumbent integer solutions which are within 99 99 feasible and well within 1 of the proven lower bound are obtained in a straightforward manner requiring on the average 30 of the mpsx time required to obtain a linear optimum

numerical calculations of critical densities for lines and planes critical percolation densities have been calculated numerically for large systems of lines in two dimensions and planes in three dimensions results for lines of varying length have been successfully predicted from the constant length case in special cases very large systems of up to 1 4 million lines have been studied by calculating critical densities for a range of system sizes and using a finite size scaling argument a prediction of the infinite critical density is made for the two dimensional system with fixed length orthogonal lines this corresponds to 3 11 intersections per line for the three dimensional system of fixed size orthogonal planes the prediction is 2 00 intersections per plane

stochastic h sub 2 h sub spl infin control with state dependent noise this paper discusses the stochastic h sub 2 h sub spl infin control problem with state dependent noise by means of the stabilization exact observability and stochastic detectability of stochastic systems the infinite horizon stochastic h sub 2 h sub spl infin control design is developed for the finite horizon h sub 2 h sub spl infin control problem our results generalize the corresponding deterministic ones to the stochastic models finally the observer based suboptimal stochastic h sub 2 h sub spl infin control is discussed in which the state variables cannot be measured directly and a feasible design algorithm is proposed

an lmi based algorithm for designing suboptimal static cal h_2 cal h_ infty output feedback controllers we consider the problem of designing a suboptimal cal h 2 cal h infty feedback control law for a linear time invariant control system when a complete set of state variables is not available this problem can be necessarily restated as a nonconvex optimization problem with a bilinear multiobjective functional under suitably chosen linear matrix inequality lmi constraints to solve such a problem we propose an lmi based procedure which is a sequential linearization programming approach the properties and the convergence of the algorithm are discussed in detail finally several numerical examples for static cal h 2 cal h infty output feedback problems demonstrate the applicability of the considered algorithm and also verify the theoretical results numerically

on stabilizability and exact observability of stochastic systems with their applications this paper mainly studies the stabilizability and exact observability of stochastic linear controlled systems and their applications with the aid of the operator spectrum a necessary and sufficient condition is given for the stabilizability of stochastic systems some new concepts such as unremovable spectrum and strong solution are introduced an unremovable spectral theorem and a stochastic popov belevith hautus criterion for exact observability are presented as applications a comparison theorem for stochastic algebraic riccati equations and a result on lyapunov type equations are obtained

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

lattice boltzmann simulation of fluid flow in fracture networks with rough self affine surfaces using the lattice boltzmann method we study fluid flow in a two dimensional 2d model of fracture network of rock each fracture in a square network is represented by a 2d channel with rough self affine internal surfaces various parameters of the model such as the connectivity and the apertures of the fractures the roughness profile of their surface as well as the reynolds number for flow of the fluid are systematically varied in order to assess their effect on the effective permeability of the fracture network the distribution of the fractures apertures is approximated well by a log normal distribution which is consistent with experimental data due to the roughness of the fractures surfaces and the finite size of the networks that can be used in the simulations the fracture network is anisotropic the anisotropy increases as the connectivity of the network decreases and approaches the percolation threshold the effective permeability k of the network follows the power law k approximately beta where is the average aperture of the fractures in the network and the exponent beta may depend on the roughness exponent a crossover from linear to nonlinear flow regime is obtained at a reynolds number re approximately o 1 but the precise numerical value of the crossover re depends on the roughness of the fractures surfaces

decentralized h_ infty filter design for discrete time interconnected fuzzy systems this paper describes a decentralized h infin filter design for discrete time interconnected fuzzy systems based on piecewise quadratic lyapunov functions the systems consist of j discrete time interconnected takagi sugeno t s fuzzy subsystems and a decentralized h infin filter is designed for each subsystem it is shown that the stability of the overall filtering error system with h infin performance can be established if a piecewise quadratic lyapunov function can be constructed moreover the parameters of filters can be obtained by solving a set of linear matrix inequalities that are numerically feasible two simulation examples are given to show the effectiveness of the proposed approach

pareto optimal filter design for nonlinear stochastic fuzzy systems via multiobjective h_ bf 2 h_ bm infty optimization this paper is concerned with the multiobjective h 2 h infty filtering design problem in nonlinear signal processing which can be approximated by a takagi sugerno t s fuzzy signal system we propose a multiobjective filter design to estimate state variables from noisy measurements for nonlinear signal systems and we focus our effort on achieving optimal concurrent performance for h 2 and h infty filtering in general it is difficult to solve the multiobjective mo h 2 h infty fuzzy filter problem directly and we therefore propose an indirect approach to minimize the upper bounds and transform the mo h 2 h infty filtering problem in to a linear matrix inequality lmi constrained multiobjective problem mop in addition we propose an lmi based multiobjective evolution algorithm to efficiently find pareto optimal solutions for the mop of multiobjective fuzzy filter design for nonlinear stochastic signal processing furthermore for comparison we also suggest the mo h 2 h infty filter design problem based on the weighted sum method our proposed indirect method can be widely employed to practically address the mo filter design problem in nonlinear signal processing finally a trajectory estimation of reentry vehicle by radar is provided to illustrate the design procedure of the pareto mo optimal filter

connectivity of fracture systems a percolation theory approach critical percolation densities have been found numerically for various systems of lines uniformly distributed in the plane the average number of intersections per line at percolation has also been found and varies only slightly over the cases considered it may therefore provide a useful rule of thumb for deciding whether a system percolates an estimate of the critical percolation density from the lattice percolation probability is presented possible extensions of the techniques described to three dimensions are discussed

an arc exchange decomposition method for multistage dynamic networks with random arc capacities abstract multistage dynamic networks with random arc capacities mdnrac have been successfully used for modeling various resource allocation problems in the transportation area however solving these problems is generally computationally intensive and there is still a need to develop more efficient solution approaches in this paper we propose a new heuristic approach that solves the mdnrac problem by decomposing the network at each stage into a series of subproblems with tree structures each subproblem can be solved efficiently the main advantage is that this approach provides an efficient computational device to handle the large scale problem instances with fairly good solution quality we show that the objective value obtained from this decomposition approach is an upper bound for that of the mdnrac problem numerical results demonstrate that our proposed approach works very well

minimum entropy static output feedback control with an h sub spl infin norm performance bound the problem of designing static output feedback controllers is considered the controller is required to minimize the closed loop entropy at s spl infin and to satisfy a prescribed h sub spl infin norm bound the design equations consist of a modified riccati equation and a lyapunov equation that are coupled via a projection these equations are solved using a homotopy algorithm the design procedure is illustrated by two examples the first one is a classical example that was solved in the literature using convex optimization techniques the second example is one of designing a gain scheduled normal acceleration loop for an air launched unmanned air vehicle

t s fuzzy bilinear model and fuzzy controller design for a class of nonlinear systems this paper proposes a fuzzy bilinear model for a class of nonlinear systems and a fuzzy controller to stabilize such systems by examination of a modeling problem we describe how to transform a nonlinear system into a bilinear one via taylor s series expansion and then we adopt the takagi sugeno t s fuzzy modeling technique to construct a fuzzy bilinear model for controller design the parallel distributed compensation pdc method is utilized to stabilize the fuzzy bilinear system fbs and some sufficient conditions are derived to guarantee the stability of the overall fuzzy control system via linear matrix inequalities lmis moreover we propound some sufficient conditions for robust stabilization of the fbs with parametric uncertainties finally a numerical example and the van de vusse model are utilized to demonstrate the validity and effectiveness of the proposed fbs

stabilization of uncertain fuzzy time delay systems via variable structure control approach in view of a recent new application of variable structure control vsc to the stabilization problem for takagi sugeno t s fuzzy models this paper aims to study the stabilization of uncertain fuzzy time delay systems in t s fuzzy model via vsc approach there are mainly two features in this paper one lies in the incorporation of time delays both smooth and nonsmooth delays in which case lyapunov functionals and razumikhin theorem are required to solve the stabilization problem the other feature is that not only matched uncertainties but also mismatched uncertainties in the state variables are considered as a sequence the contribution of this paper consists of various control schemes proposed for the vsc design and the present results are in terms of linear matrix inequalities lmis an illustrative example is given to show the effectiveness of our various results

a game theoretic approach to h control for time varying systems a representation formula for all controllers that satisfy an mathcal l infty type constraint is derived for time varying systems it is now known that a formula based on two indefinite algebraic riccati equations may be found for time invariant systems over an infinite time support see j c doyle et al ieee trans automat control ac 34 1989 pp 831 847 k glover and j c doyle systems control lett 11 1988 pp 167 172 k glover et al siam j control optim 29 1991 pp 283 324 m green et al siam j control optim 28 1990 pp 1350 1371 d j n limebeer et al in proc ieee conf on decision and control austin tx 1988 g tadmor math control systems signal processing 3 1990 pp 301 324 in the time varying case two indefinite riccati differential equations are required a solution to the design problem exists if these equations have a solution on the optimization interval the derivation of the representation formula illustrated in this paper mak

stability of fluid queueing systems with parallel servers and stochastic capacities this note introduces a piecewise deterministic queueing pdq model to study the stability of traffic queues in parallel link transportation systems facing stochastic capacity fluctuations the saturation rate capacity of the pdq model switches between a finite set of modes according to a markov chain and link inflows are controlled by a state feedback policy a pdq system is stable only if a lower bound on the time average link inflows does not exceed the corresponding time average saturation rate furthermore a pdq system is stable if the following two conditions hold the nominal mode s saturation rate is high enough that all queues vanish in this mode and a bilinear matrix inequality involving an underestimate of the discharge rates of the pdq in individual modes is feasible the stability conditions can be strengthened for two mode pdqs these results can be used for design of routing policies that guarantee stability of traffic queues under stochastic capacity fluctuations

optimal and reinforced robustness designs of fuzzy variable structure tracking control for a piezoelectric actuator system in this paper a piezoelectric actuator pea system is approximated by n subsystems which are described by pulse transfer functions the approximation error between the pea system and the fuzzy linear pulse transfer function system is represented by additive nonlinear time varying uncertainties in every subsystem first a dead beat to the switching surface for every ideal subsystem is designed it is called the variable structure tracking control the output disturbance of the ith subsystem is caused by the approximation error of fuzzy model and the interaction dynamics resulting from other subsystems in general it is not small then the h sup spl infin norm of the sensitivity function between the switching surface and the output disturbance is minimized it is the optimal robustness although the effect of the output disturbance is attenuated a better performance can be reinforced by a switching control which is based on the lyapunov redesign this is the final step for the robustness design of control which is reinforced robustness the stability of the overall system is verified by lyapunov stability theory experimental work of a pea system was carried out to confirm the validity of the proposed control

connectivity properties of two dimensional fracture networks with stochastic fractal correlation 1 we present a theoretical and numerical study of the connectivity of fracture networks with fractal correlations in addition to length distribution this spatial property observed on most fracture networks conveys long range correlation that may be crucial on network connectivity we especially focus on the model that comes out relevant to natural fracture network a fractal density distribution for the fracture centers dimension d and a power law distribution for the fracture lengths exponent a n l l a three different regimes of connectivity are identified depending on d and on a for a d 1 the connectivity is ruled by fractures much smaller than the system size with a strong control of spatial correlation the connectivity now decreases with system scale finally for the self similar case a d 1 which corresponds to the transition between the two previous regimes connectivity properties are scale invariant percolation threshold corresponds to a critical fractal density and the average number of intersections per fracture at threshold is a scale invariant as well

decentralized fuzzy control of nonlinear interconnected dynamic delay systems via mixed h_2 h_ infty optimization with smith predictor each subsystem of a nonlinear interconnected dynamic delayed system is approximated by a weighted combination of l transfer function delayed systems tfdss the h2 norm of the difference between the transfer function of a reference model and the closed loop transfer function of the kth tfds of subsystem i is then minimized to obtain a suitable frequency response without incurring oscillating and sluggish phenomena because of the existence of the disturbance at the output of the kth tfds which is not only large but also contains various frequency components the h norm of the weighted sensitivity function between the output disturbance and its corresponding output of the kth tfds is simultaneously minimized to reduce its effect furthermore with proper selection of weighted sensitivity functions certain specific modes of the output disturbance can be eliminated finally two simulations are performed one is the simulation of our designed tfdss with different delays or nonminimum phases and the other is the simulation of an internet based intelligent space for the trajectory tracking of a car like wheeled robot system we demonstrate the effectiveness and efficiency of the proposed control the main contributions of this paper are twofold first the control can simultaneously attain robust performance through the mixed h2 h optimization with a smith predictor and achieve the robust stability via l2n stable with finite gain second fuzzy observer is not needed

scenarios and policy aggregation in optimization under uncertainty a common approach in coping with multiperiod optimization problems under uncertainty where statistical information is not really enough to support a stochastic programming model has been to set up and analyze a number of scenarios the aim then is to identify trends and essential features on which a robust decision policy can be based this paper develops for the first time a rigorous algorithmic procedure for determining such a policy in response to any weighting of the scenarios the scenarios are bundled at various levels to reflect the availability of information and iterative adjustments are made to the decision policy to adapt to this structure and remove the dependence on hindsight

analysis and synthesis of nonlinear time delay systems via fuzzy control approach takagi sugeno ts fuzzy models 1985 1992 can provide an effective representation of complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear input output i o submodels in this paper the ts fuzzy model approach is extended to the stability analysis and control design for both continuous and discrete time nonlinear systems with time delay the ts fuzzy models with time delay are presented and the stability conditions are derived using lyapunov krasovskii approach we also present a stabilization approach for nonlinear time delay systems through fuzzy state feedback and fuzzy observer based controller sufficient conditions for the existence of fuzzy state feedback gain and fuzzy observer gain are derived through the numerical solution of a set of coupled linear matrix inequalities an illustrative example based on the cstr model is given to design a fuzzy controller

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

model reference output feedback fuzzy tracking control design for nonlinear discrete time systems with time delay in this study a model reference fuzzy tracking control design for nonlinear discrete time systems with time delay is introduced first the takagi and sugeno ts fuzzy model is employed to approximate a nonlinear discrete time system with time delay next based on the fuzzy model a fuzzy observer based fuzzy controller is developed to reduce the tracking error as small as possible for all bounded reference inputs the advantage of proposed tracking control design is that only a simple fuzzy observer based controller is used in our approach without feedback linearization technique and complicated adaptive scheme by the proposed method the fuzzy tracking control design problem is parameterized in terms of a linear matrix inequality problem lmip the lmip can be efficiently solved using the convex optimization techniques simulation example is given to illustrate the design procedures and tracking performance 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

robust stabilization of uncertain linear systems quadratic stabilizability and h sup infinity control theory the problem of robustly stabilizing a linear uncertain system is considered with emphasis on the interplay between the time domain results on the quadratic stabilization of uncertain systems and the frequency domain results on h sup infinity optimization a complete solution to a certain quadratic stabilization problem in which uncertainty enters both the state and the input matrices of the system is given relations between these robust stabilization problems and h sup infinity control theory are explored it is also shown that in a number of cases if a robust stabilization problem can be solved via lyapunov methods then it can be also be solved via h sup infinity control theory based methods

stochastic h infty we consider stochastic linear plants which are controlled by dynamic output feedback and subjected to both deterministic and stochastic perturbations our objective is to develop an h infty type theory for such systems we prove a bounded real lemma for stochastic systems with deterministic and stochastic perturbations this enables us to obtain necessary and sufficient conditions for the existence of a stabilizing compensator which keeps the effect of the perturbations on the to be controlled output below a given threshhold gamma 0 in the deterministic case the analogous conditions involve two uncoupled linear matrix inequalities but in the stochastic setting we obtain coupled nonlinear matrix inequalities instead the connection between h infty theory and stability radii is discussed and leads to a lower bound for the radii which is shown to be tight in some special cases

connectivity of random fault networks following a power law fault length distribution we present a theoretical and numerical study of the connectivity of fault networks following power law fault length distributions n l l a as expected for natural fault networks different regimes of connectivity are identified depending on a for a 3 faults smaller than the system size rule the network connectivity and classical laws of percolation theory apply on the opposite for a 1 the connectivity is ruled by the largest fault in the system for 1 a 3 both small and large faults control the connectivity in a ratio which depends on a the geometrical properties of the fault network and of its connected parts density scaling properties are established at the percolation threshold finally implications are discussed in the case of fault networks with constant density in particular we predict the existence of a critical scale at which fault networks are always connected whatever a smaller than 3 and whatever their fault density

online identification of continuous time systems with unknown time delay in this note we present a recursive algorithm for online identification of systems with unknown time delay the proposed algorithm can be interpreted as an approximate nonlinear least squares corresponding to modified normalized or un normalized least squares when the normalizing factor spl gamma 0 or spl gamma 0 respectively both algorithms are essentially extensions to general least squares methodology simulation studies demonstrate the characteristics and performance of these algorithms

state space solutions to standard h sub 2 and h sub infinity control problems simple state space formulas are derived for all controllers solving the following standard h sub infinity problem for a given number gamma 0 find all controllers such that the h sub infinity norm of the closed loop transfer function is strictly less than gamma it is known that a controller exists if and only if the unique stabilizing solutions to two algebraic riccati equations are positive definite and the spectral radius of their product is less than gamma sup 2 under these conditions a parameterization of all controllers solving the problem is given as a linear fractional transformation lft on a contractive stable free parameter the state dimension of the coefficient matrix for the lft constructed using the two riccati solutions equals that of the plant and has a separation structure reminiscent of classical lqg i e h sub 2 theory this paper is intended to be of tutorial value so a standard h sub 2 solution is developed in parallel

percolation thresholds of a group of anisotropic three dimensional fracture networks abstract percolation thresholds average number of connections per object of two models of anisotropic three dimensional 3d fracture networks made of mono disperse hexagons have been calculated numerically the first model is when the fracture networks are comprised of two groups of fractures that are distributed in an anisotropic manner about two orthogonal mean directions i e z and x directions we call this model bipolar anisotropic fracture network bfn the second model is when three groups of fractures are distributed about three orthogonal mean directions that is z x and y directions in this model three families of fractures about three orthogonal mean directions are oriented in 3d space we call this model tripolar anisotropic fracture network tfn the finite size scaling method is used to predict the infinite percolation thresholds the effect of anisotropicity on percolation thresholds in x y and z directions is investigated we have revealed that as the anisotropicity of networks increases the percolation thresholds in x y and z directions span the range of 2 3 to 2 0 where 2 3 and 2 0 are extremums of percolation thresholds for isotropic and non isotropic orthogonal fracture networks respectively

a dynamic network flow problem with uncertain arc capacities formulation and problem structure we consider a dynamic network flow problem where the arc capacities are random variables this gives a multistage stochastic linear program we describe the randomness using a multi scenario approach because of the multilayered structure there are several ways to decompose the linear program we classify different decomposition schemes and we develop a scheme calledcompath decomposition which is derived from path decomposition for network flows we give a polynomial time algorithm to find a cheapest compath that can solve the subproblems resulting from compath decomposition finally compath decomposition is extended to multicommodity flow problems