robust finite time h control of singular stochastic systems via static output feedback abstract this paper addresses the problem of robust finite time stabilization of singular stochastic systems via static output feedback firstly sufficient conditions of singular stochastic finite time boundedness on static output feedback are obtained for the family of singular stochastic systems with parametric uncertainties and time varying norm bounded disturbance then the results are extended to singular stochastic h finite time boundedness for the class of singular stochastic systems designed algorithm for static output feedback controller is provided to guarantee that the underlying closed loop singular stochastic system is singular stochastic h finite time boundedness in terms of strict linear matrix equalities with a fixed parameter finally an illustrative example is presented to show the validity of the developed methodology

dissipativity analysis for singular systems with time varying delays this paper is concerned with the dissipativity analysis problem for singular systems with time varying delays a delay dependent criterion is established to guarantee the dissipativity of the underlying systems using the delay partitioning technique all the results given in this paper are not only dependent upon the time delay but also dependent upon the number of delay partitions the effectiveness and the reduced conservatism of the derived results are demonstrated by two illustrative examples

design of networked control systems with packet dropouts this note is concerned with stability and controller design of networked control systems ncss with packet dropouts new ncs models are provided considering both single and multiple packet transmissions both sensor to controller s c and controller to actuator c a packet dropouts are modeled and their history behavior is described by different independent markov chains in term of the given models sufficient conditions for stochastic stability are derived in the form of linear matrix inequalities lmis and corresponding control laws are given numerical examples illustrate the effectiveness of the results

observer based h control of discrete time delay systems with random communication packet losses and multiplicative noises this paper investigates the observer based h control problem for a class of discrete time mixed delay systems with random communication packet losses and multiplicative noises where the mixed delays comprise both discrete and distributed time varying delays the random packet losses are described by a bernoulli distributed white sequence that obeys a conditional probability distribution and the multiplicative disturbances are in the form of a scalar gaussian white noise with unit variance in the presence of mixed delays random packet losses and multiplicative noises sufficient conditions for the existence of an observer based feedback controller are derived such that the closed loop control system is asymptotically mean square stable and preserves a guaranteed h performance then a linear matrix inequality lmi approach for designing such an observer based h controller is presented finally a numerical example is provided to illustrate the effectiveness of the developed theoretical results

unbiased h filtering for neutral markov jump systems abstract the unbiased h filtering problem is studied for stochastic markov jump system with constant and neutral time delays by re constructing the system the dynamic filtering error characteristics of unknown inputs and time delays are obtained a sufficient condition is initially established on the existence of mode dependent unbiased h filter of constant time delay system using stochastic lyapunov krasovskii function then the unbiased h filter is also designed for the jump system with constant and neutral time delays the design criterions are presented in the form of linear matrix inequality finally the unbiased h filtering problems are described as optimization algorithms numerical examples illustrate the effectiveness of the developed techniques

robust h control for a class of nonlinear discrete time delay stochastic systems with missing measurements this paper is concerned with the problem of robust h output feedback control for a class of uncertain discrete time delayed nonlinear stochastic systems with missing measurements the parameter uncertainties enter into all the system matrices the time varying delay is unknown with given low and upper bounds the nonlinearities satisfy the sector conditions and the missing measurements are described by a binary switching sequence that obeys a conditional probability distribution the problem addressed is the design of an output feedback controller such that for all admissible uncertainties the resulting closed loop system is exponentially stable in the mean square for the zero disturbance input and also achieves a prescribed h performance level by using the lyapunov method and stochastic analysis techniques sufficient conditions are first derived to guarantee the existence of the desired controllers and then the controller parameters are characterized in terms of linear matrix inequalities lmis a numerical example is exploited to show the usefulness of the results obtained

novel delay dependent asymptotic stability criteria for neural networks with time varying delays the problem of delay dependent asymptotic stability criteria for neural networks nns with time varying delays is investigated an improved linear matrix inequality based on delay dependent stability test is introduced to ensure a large upper bound for time delay a new class of lyapunov function is constructed to derive a novel delay dependent stability criteria finally numerical examples are given to indicate significant improvement over some existing results

linear minimum mean square filter for discrete time linear systems with markov jumps and multiplicative noises in this paper we obtain the linear minimum mean square estimator lmmse for discrete time linear systems subject to state and measurement multiplicative noises and markov jumps on the parameters it is assumed that the markov chain is not available by using geometric arguments we obtain a kalman type filter conveniently implementable in a recurrence form the stationary case is also studied and a proof for the convergence of the error covariance matrix of the lmmse to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated markov chain is obtained it is shown that there exists a unique positive semi definite solution for the stationary riccati like filter equation and moreover this solution is the limit of the error covariance matrix of the lmmse the advantage of this scheme is that it is very easy to implement and all calculations can be performed offline

h filtering of networked discrete time systems with random packet losses this paper studies the h filtering problem for networked discrete time systems with random packet losses the general multiple input multiple output mimo filtering system is considered the multiple measurements are transmitted to the remote filter via distinct communication channels and each measurement loss process is described by a two state markov chain both the mode independent and the mode dependent filters are considered and the resulting filtering error system is modelled as a discrete time markovian system with multiple modes a necessary and sufficient condition is derived for the filtering error system to be mean square exponentially stable and achieve a prescribed h noise attenuation performance the obtained condition implicitly establishes a relation between the packet loss probability and two parameters namely the exponential decay rate of the filtering error system and the h noise attenuation level a convex optimization problem is formulated to design the desired filters with minimized h noise attenuation level bound finally an illustrative example is given to show the effectiveness of the proposed results

technical communique reliable h control for discrete time piecewise linear systems with infinite distributed delays in this paper the reliable h control problem is investigated for discrete time piecewise linear systems with time delays and actuator failures the time delays are assumed to be infinitely distributed in the discrete time domain and the possible failure of each actuator is described by a variable varying in a given interval the aim of the addressed reliable h control problem is to design a controller such that for the admissible infinite distributed delays and possible actuator failures the closed loop system is exponentially stable with a given disturbance attenuation level c the controller gain is characterized in terms of the solution to a linear matrix inequality that can be easily solved by using standard software packages a simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures

passivity analysis for discrete time stochastic markovian jump neural networks with mixed time delays in this paper passivity analysis is conducted for discrete time stochastic neural networks with both markovian jumping parameters and mixed time delays the mixed time delays consist of both discrete and distributed delays the markov chain in the underlying neural networks is finite piecewise homogeneous by introducing a lyapunov functional that accounts for the mixed time delays a delay dependent passivity condition is derived in terms of the linear matrix inequality approach the case of markov chain with partially unknown transition probabilities is also considered all the results presented depend upon not only discrete delay but also distributed delay a numerical example is included to demonstrate the effectiveness of the proposed methods

feedback and optimal sensitivity model reference transformations multiplicative seminorms and approximate inverses in this paper the problem of sensitivity reduction by feedback is formulated as an optimization problem and separated from the problem of stabilization stable feedback schemes obtainable from a given plant are parameterized salient properties of sensitivity reducing schemes are derived and it is shown that plant uncertainty reduces the ability of feedback to reduce sensitivity the theory is developed for input output systems in a general setting of banach algebras and then specialized to a class of multivariable time invariant systems characterized by n times n matrices of h infty frequency response functions either with or without zeros in the right half plane the approach is based on the use of a weighted seminorm on the algebra of operators to measure sensitivity and on the concept of an approximate inverse approximate invertibility of the plant is shown to be a necessary and sufficient condition for sensitivity reduction an indicator of approximate invertibility called a measure of singularity is introduced the measure of singularity of a linear time invariant plant is shown to be determined by the location of its right half plane zeros in the absence of plant uncertainty the sensitivity to output disturbances can be reduced to an optimal value approaching the singularity measure in particular if there are no right half plane zeros sensitivity can be made arbitrarily small the feedback schemes used in the optimization of sensitivity resemble the lead lag networks of classical control design some of their properties and methods of constructing them in special cases are presented

robust h_ infty control with missing measurements and time delays in this technical note the robust control problem is investigated for a class of stochastic uncertain discrete time delay systems with missing measurements the parameter uncertainties enter into the state matrices and the missing measurements are described by a binary switching sequence satisfying a conditional probability distribution the purpose of the problem is to design a full order dynamic feedback controller such that for all possible missing observations and admissible parameter uncertainties the closed loop system is asymptotically mean square stable and satisfies the prescribed performance constraint delay dependent conditions are derived under which the desired solution exists and the controller parameters are designed by solving a linear matrix inequality lmi a numerical example is provided to illustrate the usefulness of the proposed design method

robust h control of discrete switched system with time delay this paper deals with the stabilization and robust h infinity control of discrete switched system with time delay the switching is time driven and the design is based on the average dwell time method the controller parameters and the permissible switching sequence subject to the given average dwell time can be obtained by solving a set of linear matrix inequalities lmis two examples are given to demonstrate the proposed methods

technical communique h output feedback control of discrete time systems with state multiplicative noise linear discrete time systems with stochastic uncertainties in their state space model are considered the problem of dynamic output feedback control is solved via a new approach for both the finite horizon and the stationary cases in both cases a cost function is defined which is the expected value of the standard h performance index with respect to the uncertain parameters an example is given which demonstrates the applicability of the theory

exponential synchronization of neural networks with discrete and distributed delays under time varying sampling this paper investigates the problem of master slave synchronization for neural networks with discrete and distributed delays under variable sampling with a known upper bound on the sampling intervals an improved method is proposed which captures the characteristic of sampled data systems some delay dependent criteria are derived to ensure the exponential stability of the error systems and thus the master systems synchronize with the slave systems the desired sampled data controller can be achieved by solving a set of linear matrix inequalitys which depend upon the maximum sampling interval and the decay rate the obtained conditions not only have less conservatism but also have less decision variables than existing results simulation results are given to show the effectiveness and benefits of the proposed methods

robust h exponential filtering for uncertain stochastic time delay systems with markovian switching and nonlinearities in this paper we deal with the robust h exponential filtering problem for a class of uncertain stochastic time delay systems with markovian switching and nonlinear disturbances the system under consideration involves parameter uncertainties ito type stochastic disturbances markovian jump parameters unknown nonlinear disturbances as well as time varying delays which vary in a range and dependent on the mode of the operation the aim of this problem is to design a markovian jump exponential filter such that the filtering error system is robustly stochastically exponentially mean square stable and a prescribed h disturbance attenuation level is guaranteed novel delay range dependent sufficient conditions are proposed to guarantee the existence of the desired robust exponential filter which are derived in terms of linear matrix inequalities lmis then the explicit expression of the desired filter parameters is characterized an illustrative numerical example is provided to demonstrate the effectiveness of the proposed method

a delay dependent approach to robust h sub spl infin filtering for uncertain discrete time state delayed systems a delay dependent approach to robust h sub spl infin filtering is proposed for linear discrete time uncertain systems with multiple delays in the state the uncertain parameters are supposed to reside in a polytope and the attention is focused on the design of robust filters guaranteeing a prescribed h sub spl infin noise attenuation level the proposed filter design methodology incorporates some recently appeared results such as moon s new version of the upper bound for the inner product of two vectors and de oliveira s idea of parameter dependent stability which greatly reduce the overdesign introduced in the derivation process in addition to the full order filtering problem the challenging reduced order case is also addressed by using different linearization procedures both full and reduced order filters can be obtained from the solution of convex optimization problems in terms of linear matrix inequalities which can be solved via efficient interior point algorithms numerical examples have been presented to illustrate the feasibility and advantages of the proposed methodologies

robust stability with structured real parameter perturbations this paper considers the problem of robust stabilization of a linear time invariant system subject to variations of a real parameter vector for a given controller the radius of the largest stability hypersphere in this parameter space is calculated this radius is a measure of the stability margin of the closed loop system the results developed are applicable to all systems where the closed loop characteristic polynomial coefficients are linear functions of the parameters of interest in particular this always occurs for single input multioutput or single output multiinput systems where the transfer function coefficients are linear or affine functions of the parameters many problems with transfer function coefficients which are nonlinear functions of physical parameters can be cast into this mathematical framework by suitable weighting and redefinition of functions of physical parameters as new parameters the largest stability hyperellipsoid for the case of weighted perturbations and a stability polytope in parameter space are also determined based on these calculations a design procedure is proposed to robustify a given stabilizing controller this algorithm iteratively enlarges the stability hypersphere or hyperellipsoid in parameter space and can be used to design a controller io stabilize a plant subject to given ranges of parameter excursions these results are illustrated by an example

robust variance constrained h control for stochastic systems with multiplicative noises abstract in this paper the robust variance constrained h control problem is considered for uncertain stochastic systems with multiplicative noises the norm bounded parametric uncertainties enter into both the system and output matrices the purpose of the problem is to design a state feedback controller such that for all admissible parameter uncertainties 1 the closed loop system is exponentially mean square quadratically stable 2 the individual steady state variance satisfies given upper bound constraints and 3 the prescribed noise attenuation level is guaranteed in an h sense with respect to the additive noise disturbances a general framework is established to solve the addressed multiobjective problem by using a linear matrix inequality lmi approach where the required stability the h characterization and variance constraints are all easily enforced within such a framework two additional optimization problems are formulated one is to optimize the h performance and the other is to minimize the weighted sum of the system state variances a numerical example is provided to illustrate the effectiveness of the proposed design algorithm

variance constrained filtering for uncertain stochastic systems with missing measurements in this note we consider a new filtering problem for linear uncertain discrete time stochastic systems with missing measurements the parameter uncertainties are allowed to be norm bounded and enter into the state matrix the system measurements may be unavailable i e missing data at any sample time and the probability of the occurrence of missing data is assumed to be known the purpose of this problem is to design a linear filter such that for all admissible parameter uncertainties and all possible incomplete observations the error state of the filtering process is mean square bounded and the steady state variance of the estimation error of each state is not more than the individual prescribed upper bound it is shown that the addressed filtering problem can effectively be solved in terms of the solutions of a couple of algebraic riccati like inequalities or linear matrix inequalities the explicit expression of the desired robust filters is parameterized and an illustrative numerical example is provided to demonstrate the usefulness and flexibility of the proposed design approach

a simulation based evolutionary approach to lna circuit design optimization abstract in this paper we propose a simulation based evolutionary approach for designing low noise amplifier lna integrated circuits ics based on a genetic algorithm ga the levenberg marquardt lm method and a circuit simulator the simulation based evolutionary approach is developed for design optimization of lna circuits for a given lna circuit the simulation based evolutionary approach simultaneously optimizes the electrical specifications such as s 11 s 12 s 21 s 22 k factor the noise figure and the input third order intercept point in the process between simulation and optimization first of all the necessary parameters of the lna circuit for circuit simulation are loaded by solving a set of nonlinear ordinary differential equations the circuit simulator will then be performed for the circuit simulation and specification evaluation once the specification meets the aforementioned seven constraints we output the optimized parameters otherwise we activate the ga for the global optimization in the meanwhile the lm method searches the local optima according to the results of the ga we then call circuit simulator to compute and evaluate newer results until the specification is matched in numerical experiment 10 parameters of the lna circuit including device configuration and biasing condition are optimized with respect to the constraints the design of lna circuit is with 0 18 m metal oxide silicon filed effect transistors benchmark results also computationally confirm the robustness and efficiency of the proposed method this simulation based evolutionary approach in general can be applied to optimal design of other analog and radio frequency circuits we believe that this systematical approach will help ic design optimization and benefit computer aided design of wireless communication system on a chip