on 2 d pole placement the problem of characteristic polynomial assignment by dynamic output feedback in 2 d systems is solved via 2 d polynomial methods a simple necessary and sufficient condition is given the class of all assignable characteristic polynomials is described in a parametric form stable and causal solutions are treated

evaluating naval tactical missile systems by fuzzy ahp based on the grade value of membership function abstract many decision making problems which are complicated and fuzzy in nature exist in modern society how to solve them is becoming increasingly important for human society for solving multiple criteria s decision making in a fuzzy environment in this paper we will propose a new algorithm for evaluating naval tactical missile systems by the fuzzy analytical hierarchy process based on grade value of membership function generally we are given scores by experience of experts to represent judgmental objects in this paper from viewpoint of many experts we will build membership functions of judgement criteria for all sub items when the membership function is built we can calculate the grade value by data of missile performance the grade value is called performance score our methods can be summarized in the following 1 1 building membership function of judgement criteria for all sub items it is called fuzzy standard 2 2 calculate the grade of membership function by practical data to represent performance scores 3 3 use fuzzy ahp method and entropy concepts to calculate aggregate weights finally for a simple and efficient computation we have developed a systematic and practical program to calculate all algorithms and apply the new algorithm to a naval tactical missile systems valuation and selection problem

coefficient assignment of 2 d systems by periodic feedback the coefficient assignment problem by periodic feedback for 2 d linear systems described by the roesser model is considered sufficient conditions for the existence of a solution to the problem are established a procedure for finding a sequence of feedback gain matrices is presented and illustrated by a numerical example

well posedness of feedback systems insights into exact robustness analysis and approximate computations this paper establishes a framework for robust stability analysis of linear time invariant uncertain systems the uncertainty is assumed to belong to an arbitrary subset of complex matrices the concept used here is well posedness of feedback systems leading to necessary and sufficient conditions for robust stability based on this concept some insights into exact robust stability conditions are given in particular frequency domain and state space conditions for well posedness are provided in terms of hermitian form inequalities it is shown that these inequalities can be interpreted as small gain conditions with a generalized class of scalings given by linear fractional transformations lft using the lft scaled small gain condition in the state space setting the duality is established between the h sub spl infin norm condition with frequency dependent scalings and the parameter dependent lyapunov condition connections to the existing results including the structured singular value and the integral quadratic constraints are also discussed finally we show that our well posedness conditions can be used to give a less conservative yet computable bound on the real structured singular value this result is illustrated by numerical examples

2 d exact model matching the exact model matching problem in single input single output 2 d systems is solved by applying polyaomial techniques all solutions are described in a parametric form natural solvability conditions for causal and or stable solutions are given and a simple design procedure is proposed it consists in solving a linear 2 d polynomial equation which directly yields a suitable compensator

on the assignment of invariant factors by time varying feedback strategies abstract in this paper the realization of arbitrary invariant factors or cyclic components of the closed loop system matrix is discussed it is shown that the use of time varying feedback strategies enables one to realize arbitrary invariant factors in contrast with time invariant feedback control

separability assignment problem for q dimensional linear discrete time systems separability assignment problem for q dimensional system is formulated sufficient conditions for the existence of a solution to the problem are presented an algorithm for finding the feedback gain matrix is given and illustrated by an example of a 4 d system

note on the pole assignment of q dimensional linear systems the method in chu 1986 for the solution of the pole assignment problem of separable 2 d linear discrete systems with state feedback is improved and extended to q d linear discrete systems and systems with output feedback

fuzzy hierarchical analysis the lambda max method abstract we present a new method of finding the fuzzy weights in fuzzy hierarchical analysis which is the direct fuzzification of the max method used by saaty in the analytical hierarchical process an example is presented where there are five criteria and three alternatives

robust mixed generalized h sub 2 h sub spl infin filtering of 2 d nonlinear fractional transformation systems this study considers robust filtering problems for uncertain two dimensional 2 d discrete systems in nonlinear fractional transformation nft representations like one dimensional 1 d systems the nft in this paper serves to complement the linear fractional transformation lft linear matrix inequality lmi formulations are given to analyze as well as synthesize robust filters numerical examples show the advantage of the nft over the lft in terms of not only computational savings but also substantial performance gains and verify the efficiency of the proposed techniques

n d polynomial matrix equations linear matrix equations in the ring of polynomials in n indeterminates n d are studied general and minimum degree solutions are discussed simple and constructive necessary and sufficient solvability conditions are derived an algorithm to solve the equations with general n d polynomial matrices is presented it is based on elementary reductions in a greater ring of polynomials in one indeterminate having as coefficients polynomial fractions in the other n 1 indeterminates which makes the use of euclidean division possible

fuzzy system reliability analysis by interval of confidence abstract the use of fuzzy number over interval of confidence instead of probability and possibilitic considerations for evaluating the range value and interval of the fuzzy reliability is proposed this approach of evaluating fuzzy system reliability by interval arithmetic and cuts has a considerable advantage we can calculate reliability problems easily by the use of derive and mathcad packages through theoretical analysis an illustrative example and computational results we show that the proposed approach is more general and simplified

matrix assignment for 2 d systems with periodically variable coefficients by periodic feedback abstract the matrix assignment problem by periodic state feedback for 2 d linear systems with periodically variable coefficients is considered it is shown that an arbitrary matrix can be assigned by periodic state feedback if the system is locally controllable a procedure for finding a sequence of feedback gain matrices is presented and illustrated by a numerical example

pole placement for linear discrete time systems by periodic output feedbacks abstract necessary and sufficient conditions for the existence of a solution to the pole placement problem by periodic output feedbacks for single input single output linear discrete time systems are established an algorithm for finding a sequence of output feedback gains is presented and illustrated by a simple numerical example

evaluating attack helicopters by ahp based on linguistic variable weight abstract in this paper we propose a new method for evaluating weapon systems by analytical hierarchy process ahp based on linguistic variable weight many researchers used fuzzy arithmetic operations with weight and attribute of computing performance score to solve fuzzy madm problems such as s m chen evaluating weapon systems using fuzzy arithmetic operations fuzzy sets and systems 77 1996 265 276 chen used a large number of fuzzy arithmetic operations which not only causes information data loss or more fuzziness but also adds to the difficulty and accuracy of decision making therefore we use linguistic variable weight method to solve the above problems and to avoid the mistake of decision making our method possesses intuition in accord with human rethinking model and is close to humanized uncertainty of language expression we use many experts viewpoints to build the membership function in order to calculate the performance score and identify expectation of the decision maker to avoid the constraint of system alternatives and subjective judgements of the decision maker in this paper we also use linguistic variable method to revise the method of c h cheng in proceedings of the fourth national conference on defense management pp 1113 1124 and r r yager fuzzy sets and systems 1 1978 87 95 firstly we measure the importance of relative weight and use it to determine the centralization or dilation power of linguistic hedge when the power of linguistic hedge is determined we can use it to calculate the results of decision making finally we construct a practical example for evaluating attack helicopters to illustrate our proposed method

robust stability of sampled data systems under possibly unstable additive multiplicative perturbations applies the fr operator technique to the robust stability problem of sampled data systems against additive multiplicative perturbations where a reasonable class of perturbations consists of unstable as well as stable ones assuming that the number of unstable modes of the plant does not change we show that a small gain condition in terms of the fr operator representation which is actually equivalent to a small gain condition in terms of the l sub 2 induced norm is still necessary and sufficient for the sampled data system to be robustly stable against h periodic perturbations in spite of their possible instability the result is derived by a nyquist type of arguments next a necessary and sufficient condition for robust stability against linear time invariant lti perturbations is also given furthermore we show that if the plant is either single input or single output the condition can be reduced to a readily testable form finally we clarify when the small gain condition becomes a particularly poor measure for robust stability

self tuning prediction and control for two dimensional processes part 1 fixed parameter algorithms least squares optimal prediction minimum variance control and generalized minimum variance control algorithms for a two dimensional carma process are developed each algorithm involves the algebraic solution of a two dimensional diophantine equation and may be embedded within classical two dimensional systems theory we show how the algorithms must be modified for any practical implementation to take into account the edges of the data field in this case we show how we may analyse the process using multivariable theory and explore the linkages between multivariable representations and two dimensional systems

a function space approach to sampled data control systems and tracking problems this paper presents a new framework for hybrid sampled data control systems instead of considering the state only at sampling instants this paper introduces a function piece during the sampling period as the state and gives an infinite dimensional model with such a state space this gives the advantage that sampled data systems with built in intersample behavior can be regarded as linear time invariant discrete time systems as a result the approach makes it possible to introduce such time invariant concepts as transfer functions poles and zeros to the sampled data systems even with the presence of the intersample behavior in particular tracking problems can be studied in this setting in a simple and unified way and ripples are completely characterized as a mismatch between the intersample reference signal and transmission zero directions this leads to the internal model principle for sampled data systems

pole assignment problem in two dimensional linear systems sufficient conditions for existence of a solution to the pole assignment problem in a class of 2 d linear systems using state feedback are given an algorithm for finding the feedback gain matrix for a class of 2 d linear systems is presented and illustrated by simple numerical example

evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight abstract the performance evaluation of weapon systems are multiple criteria decision making problems the descriptions and judgements on weapon systems are usually linguistic and fuzzy the traditional method of analytic hierarchy process ahp are mainly used in crisp non fuzzy decision applications with a very unbalanced scale of judgements to overcome these problems we will propose a new and general decision making method for evaluating weapon systems using fuzzy ahp based on entropy weight we will use symmetric triangular fuzzy number 1 to 9 to indicate the relative strength of the elements in the hierarchy and build fuzzy judgement vectors matrix through comparison of the performance scores we will derive the priority among the alternatives by the entropy weight through the use of interval arithmetic cuts and index of optimism the degree of optimism of the decision maker to estimate the degree of satisfaction of the judgement in this way it does not require a series of pairwise comparison judgements as required by the traditional ahp method by multiplying the fuzzy subjective weight vector w with the corresponding fuzzy judgement matrix x the orderly list of fuzzy judgement vectors x i for every criterion ci a fuzzy problem can be solved and a weapon system selection example will be used to illustrate our method and compare it with other methods

existence conditions and properties of the frequency response operators of continuous time periodic systems the definition of the frequency response operator via the steady state analysis in finite dimensional linear continuous time periodic fdlcp systems is revisited it is shown that the frequency response operator is guaranteed to be well defined only densely on the linear space l2 which is different from the usual understanding fortunately however it turns out that this frequency response operator can have an extension onto l2 so that the equivalence between the time domain h2 norm respectively the l2 induced norm and the frequency domain h2 norm respectively the h infty norm of the frequency response operator is recovered under some stronger assumptions it is also shown that the frequency response operator can be viewed as a bounded operator from l1 to l1 which can also be established via the steady state analysis

minimum energy control of 2 d linear systems with variable coefficients the definition of the state transition matrix for roesser s model of 2 d systems with variable coefficients is introduced and the general response formula is derived necessary and sufficient conditions for local controllability are formulated the minimum energy control problem for roesser s model of 2 d systems with variable coefficients is formulated and solved

characteristic polynomial assignment and determination of the residual polynomial in 2 d systems an approach is presented for simultaneously solving the characteristic polynomial assignment problem and the problem of determining the residual polynomial i e the unassignable part of the open loop characteristic polynomial in 2 d systems

fuzzy hierarchical analysis revisited abstract we present a new method of finding the fuzzy weights in fuzzy hierarchical analysis which is the direct fuzzification of the original method used by saaty in the analytic hierarchy process we test our new procedure in two cases where there are formulas for the crisp weights an example is presented where there are five criteria and three alternatives

nyquist stability criterion and positive realness of sampled data systems abstract in this paper we first derive a nyquist stability criterion of sampled data systems in such a form that reflects the treatment of sampled data systems with their intersample behavior taken into account we next analyze the positive realness of sampled data systems with d 11 matrix i e the continuous time direct feedthrough matrix from the disturbance input w to the controlled output z being 0 and show that such sampled data systems cannot be made positive real unless the relative degree of the system from w to z is 1 we further show that adding some appropriate d 11 leads to positive real sampled data systems and give a method to find such d 11 that is as small as possible this should be useful for the stability analysis of sampled data systems with nonlinearities all these analyses as well as the small gain analysis are compared from the viewpoint of the gain margin analysis

optimization problems in partially ordered hilbert resolution spaces recent studies hove introduced the concept of a partially ordered hilbert resolution space as a means of modelling the behaviour of multidimensional systems the present study utilizes this framework to formulate and solve some typical optimization problems the resultant solutions provide design criteria for multidimensional systems and highlight both the similarities and the differences between the single dimensional and multidimensional cases

one more counterexample in n d systems unimodular versus elementary operations by a simple counterexample it is shown that there are unimodular matrices which cannot be written as products of elementary matrices in the ring of n d polynomials as a consequence some methods for the solution of n d matrix polynomial equations published recently which are based on the elementary operations in the ring of n d polynomials do not work

h sub spl infin filtering of 2 d discrete systems this paper deals with h sub spl infin filtering of two dimensional 2 d linear discrete systems described by a 2 d local state space lss fornasini marchesini 1978 second model several versions of the bounded real lemma of the 2 d discrete systems are established the 2 d bounded real lemma allows us to solve the finite horizon and infinite horizon h sub spl infin filtering problems using a riccati difference equation or a riccati inequality approach further a solution to the infinite horizon h sub spl infin filtering problem based on a linear matrix inequality lmi approach is developed our results extend existing work for one dimensional 1 d systems to the 2 d case and give a state space solution to the bounded realness of 2 d discrete systems as well as 2 d h sub spl infin filtering for the first time numerical examples are given to demonstrate the riccati difference equation approach to the 2 d finite horizon h sub spl infin filtering problem and the lmi approach to the 2 d infinite horizon h sub spl infin filtering problem

asymptotic tracking for 2 d and delay differential systems abstract a method for asymptotic tracking in 2 d systems is presented and is applied to discrete 2 d systems and delay differential systems the method consists of solving two linear equations in 2 d polynomials solvability conditions are derived and the questions of stability causality and properness are discussed

linear periodically time varying scaling and its properties stimulated by a general necessary and sufficient condition for robust stability of sampled data systems stated in an operator theoretic framework we introduce a novel technique called linear periodically time varying lptv scaling we then give a simple example of sampled data systems in which this new scaling allows exact robust stability analysis for static uncertainties while the conventional linear time invariant lti scaling fails to do so this leads us to an interesting question whether lptv scaling can be effective also in other situations e g in the robust stability analysis of continuous time feedback systems regarded as a special class of sampled data systems or for other classes of uncertainties we thus study some basic properties of lptv scaling by confining ourselves to the so called d scaling and show that it provides no advantage over lti scaling when it is applied to continuous time lti feedback systems regardless of the class of uncertainties we take into consideration this demonstrates that the lptv scaling of the type we deal with in this paper is in some sense a special technique for sampled data systems but is indeed an effective and more natural technique than the conventional lti scaling as far as such systems are concerned the technique can be further extended to include what is called noncausal lptv scaling and the implication of the present study in such a larger framework of lptv scaling is also described

brief paper noncausal linear periodically time varying scaling for robust stability analysis of discrete time systems frequency dependent scaling induced by static separators this article is concerned with robust stability analysis of discrete time systems and introduces a novel and powerful technique that we call noncausal linear periodically time varying lptv scaling based on the discrete time lifting together with the conventional but general scaling approach we are led to the notion of noncausal lptv scaling for lptv systems and its effectiveness is demonstrated with a numerical example to separate the effect of noncausal and lptv characteristics of noncausal lptv scaling to see which is a more important source leading to the effectiveness we then consider the case of lti systems as a special case then we show that even static noncausal lptv scaling has an ability of inducing frequency dependent scaling when viewed in the context of the conventional lti scaling while causal lptv scaling fails to do so it is further discussed that the effectiveness of noncausal characteristics leading to the frequency domain interpretation can be exploited even for lptv systems by considering the nn lifted transfer matrices of n periodic systems

brief paper separator type robust stability theorem of sampled data systems allowing noncausal lptv scaling this paper derives a necessary and sufficient condition for robust stability of sampled data systems which is stated by using the notion of separators that are dealt with in an operator theoretic framework such operator theoretic treatment of separators provides a new perspective which we call noncausal linear periodically time varying scaling and leads to reducing conservativeness in robust stability analysis a numerical example is given to demonstrate the results

evaluating weapon systems using ranking fuzzy numbers abstract in this paper we will point out that chen s 1996 paper has some errors a weapon system is large and complex it has multi level multi factor and multi hierarchy features chen s method does not normalize each criterion s scores which will make a wrong decision under the following conditions i there are many levels for rank scores ii a criterion has many factors iii the total scores of systems have a larger difference under this criterion and iv one criterion s weight is larger than the other criteria numerical illustration is shown in section 5 therefore chen s method is not a general method for the evaluation of weapon systems after pointing out some errors in chen s paper to overcome these errors we will revise it and propose a general method for the evaluation of weapon systems our method utilizes fuzzy ratio scales 1 3 5 7 9 the goal is normalizing heterogeneity into homogeneity to indicate the relative strength of the factors in the corresponding criteria then we build a judgement matrix through comparison of the total scores of performance and use 1 3 5 7 9 to represent a weight vector among these criteria we will derive the priority among the alternatives by multiplying the fuzzy judgement matrix with the corresponding fuzzy weight vector the final results become a problem of ranking fuzzy numbers many triangular fuzzy numbers can easily rank its ordering by the intuition ranking method lee and li 1988 pointed out that human intuition would favor a fuzzy number with the following characteristics higher mean value and at the same time lower spread if its ordering cannot rank by figures we can use many other methods of ranking fuzzy numbers therefore the best weapon selection can be obtained by ranking fuzzy numbers

an algorithm for the computation of 2 d eigenvalues in this paper a definition for the eigenvalues of two dimensional 2 d general discrete state space models is proposed this definition is consistent with that known for 2 d roesser models also a programmable algorithm is developed to compute the 2 d eigenvalues

quasi finite rank approximation of compression operators in sampled data systems and time delay systems this article studies an approximation problem of compression operators that play important roles in the operator theoretic approach to sampled data systems and time delay systems taking account of the ease in the use of approximated operators in such an approach we confine ourselves to a special form of approximation that we call quasi finite rank approximation we first introduce a suboptimal method for such approximation by means of what we call the fast lifting approach with which the problem can be reduced to a finite dimensional one in an approximate sense we further introduce another method that somehow applies the first method in a nested fashion for better overall performance we also discuss the asymptotic exactness of the suboptimal optimisation methods as the integer parameter m in the fast lifting approach tends to infinity as well as the associated monotonic properties as to the reduction of the deviation from the optimal approximation numerical examples are given to demonstrate the eff

the entropy change of fuzzy numbers with arithmetic operations for the same type of two fuzzy sets with different supports this paper investigates the entropy relationship between both of them for the fuzzy numbers with triangular membership function the entropy change between the resultant fuzzy numbers through some arithmetic operations and the original fuzzy numbers is also studied

2 regularized nyquist criterion in linear continuous time periodic systems and its implementation first by using the 2 regularized determinant technique for hilbert schmidt operators the computation formula infinite product convergence and analyticity of the 2 regularized determinant of the modified harmonic state operator in finite dimensional linear continuous time periodic fdlcp systems are derived in this paper second based on these results a 2 regularized nyquist criterion is established for asymptotic stability analysis of a class of fdlcp systems for the first time third a numeric implementation algorithm for the 2 regularized nyquist criterion is also proposed via the staircase truncation on the harmonic transfer operator of the fdlcp system concerned finally to illustrate the results of this paper asymptotic stability of the lossy mathieu differential equation is investigated

entropy variation on the fuzzy numbers with arithmetic operations entropy is always the measure of the fuzziness degree for a fuzzy set this paper studies the entropy variation on the fuzzy numbers or fuzzy sets under the following several cases i two fuzzy sets on the same type but different support size ii the addition of finite number of fuzzy numbers on the same type iii the subtraction of finite number of fuzzy numbers on the same type iv the multiplication of a constant and a fuzzy number it is shown that through the above arithmetic operations the resultant fuzzy number is the same type as the original fuzzy numbers and the entropy of the resultant fuzzy number has the arithmetic relation with the entropy of each original fuzzy number

a pole assignment problem for 2 dimensional linear discrete systems in kaczorek 1983 the pole assignment problem of a class of 2 dimensional linear discrete systems is solved in this paper an algorithm for a larger class of systems is presented if degrees of freedom permit the most robust feedback gain matrix can be found numerical examples are included

generalized model matching and f g invariant submodules for linear systems over rings abstract a generalized version of the exact model matching problem gemmp is considered for linear multivariable systems over an arbitrary commutative ring k with identity reduced forms of this problem are introduced and a characterization of all solutions and minimal order solutions is given both with and without the properness constraint on the solutions in terms of linear equations over k and k modules an approach to the characterization of all stable solutions is presented which under a certain bezout condition and a freeness condition provides a parametrization of all stable solutions the results provide an explicit parametrization of all solutions and all stable solutions in case k is a field without the bezout condition this is achieved through a very simple characterization and a generalization to an arbitrary field k of the fixed poles of the model matching problem in terms of invariant factors of a certain polynomial matrix the results also show that whenever the gemmp has a solution there exist solutions whose poles can be chosen arbitrarily as far as they contain the fixed poles with the right multiplicities in the algebraic closure of k implications of these results in regard to inverse systems are shown equivalent simpler forms in state space form of the problem are shown to be obtainable a theory of finitely generated f g invariant submodules for linear systems over rings is developed and the geometric equivalent of the model matching problem the dynamic cover problem is formulated to which the results of the previous sections provide a solution in the reduced case

angular factorization of matrices let q denote a selfadjoint matrix or operator of finite rank the factorization of i q into the form i q i w d i w is considered the well known case where w is constrained to be lower triangular while d is diagonal is extended to quadrangular and other generalized canonical forms the case where q is not selfadjoint is also developed applications for these results may be found in the realm of multivariate stochastic approximation and signal extraction

robust pole assignment in linear state feedback numerical methods are described for determining robust or well conditioned solutions to the problem of pole assignment by state feedback the solutions obtained are such that the sensitivity of the assigned poles to perturbations in the system and gain matrices is minimized it is shown that for these solutions upper bounds on the norm of the feedback matrix and on the transient response are also minimized and a lower bound on the stability margin is maximized a measure is derived which indicates the optimal conditioning that may be expected for a particular system with a given set of closed loop poles and hence the suitability of the given poles for assignment

state estimation in discrete m d systems in this study observers and stochastic state estimation for m d systems are considered the analysis uses a wave advance process model in transporting the existing 1 d results to the m d setting a constrained minimization technique is used to compute the optimal state estimator which preserves quarter plane causality the optimal state estimator without the quarter plane causality constraint is also determined a comparison then yields insight into the tradeoff between quarter plane causality and estimator performance

a complete analytical solution to the equation ta ft lc and its applications in this note a complete analytical and restriction free solution with complete and explicit freedom of the matrix equation ta ft lc is proposed here a c is given and is observable and f is in the jordan form with arbitrary given eigenvalues this solution appears to be new because it can be applied directly to obtain significantly better solutions to the following three basic design problems 1 2 d system eigenvalue assignment 2 function observer design and 3 state feedback eigenstructure design as shown in this note

robust mixed spl hscr sub 2 spl hscr sub spl infin filtering of 2 d systems this paper deals with several challenging problems of robust filtering for two dimensional 2 d systems first of all new linear matrix inequality lmi characterizations for the spl hscr sub spl infin and spl hscr 2 norms of 2 d systems are introduced and thoroughly established based on these preparatory results convex lmi characterizations for robust spl hscr sub spl infin spl hscr sub 2 and robust mixed spl hscr sub 2 spl hscr sub spl infin filtering are derived the efficiency and viability of the proposed techniques and tools are demonstrated through a set of numerical examples

evaluating weapon systems using fuzzy arithmetic operations in this paper we present a new method to deal with the performance evaluation of weapon systems using fuzzy arithmetic operations an example of tactical missile systems selection is used to illustrate the performance evaluation process of weapon systems because the proposed methods uses simplified fuzzy arithmetic operations of fuzzy numbers rather than the complicated entropy weight calculations mentioned in 7 its execution is much faster than the one presented in 7

pole assignment of two dimensional systems for separable characteristic equations abstract this paper considers the problem of pole assignment of linear time invariant multivariable two dimensional systems the desirable closed loop characteristic function is considered to be separable an algorithm is presented for the solution of the problem using state feedback the necessary condition for the problem to have a solution is established and an illustrative example is given

solution to the 2 d eigenvalue assignment problem a method for eigenvalue assignment by state feedback for 2 d systems described by the roesser model is proposed an algorithm for the choice of the state feedback matrix has been provided and illustrated by a numerical example

pole assignment for systems over rings a very simple proof of the pole assignment theorem for systems over a principal ideal domain and other rings is given furthermore an algorithm is presented extensions are also indicated

regulation of split linear systems over rings coefficient assignment and observers a theory of regulators is developed for finite free split linear systems over a commutative ring k this is achieved by developing a theory of coefficient assignment and observers it is shown that the problem of coefficient assignment can be solved for reachable systems by using dynamic state feedback for strongly observable systems it is shown that observers with arbitrary dynamics can be constructed internal stability of observer and state feedback configuration is considered explicitly some examples are given to illustrate these techniques

robust filtering for 2 d state delayed systems with nft uncertainties this paper is concerned with the robust filtering problem for two dimensional 2 d state delayed systems with uncertainties represented by nonlinear fraction transformation the authors first establish the stability h sub spl infin performance and generalized h sub 2 performance criteria for the system based on the results the authors propose efficient methods to solve the robust h sub spl infin filtering generalized h sub 2 filtering and mixed generalized h sub 2 h sub spl infin filtering problems by using a parameter dependent lyapunov function approach the methods involve solving linear matrix inequalities two examples are given to show the effectiveness of the proposed approach

coordinated one step optimal distributed state prediction for a networked dynamical system a new recursive one step state prediction procedure is derived for a networked dynamic system under the coordination of a collaboration unit that provides optimal update gains for each individual subsystem utilizing merely system parameters this predictor estimates plant s local states based only on local system output measurements this estimator can be easily realized in a distributed way and can also be simply scaled to systems with a large amount of subsystems provided it has enough communication and storage capacities it is proved that when prediction error variances are adopted in performance comparisons the optimal gain matrix is usually unique recursive and explicit expressions are derived for both this optimal gain matrix and the covariance matrix of the corresponding prediction errors the optimal gain matrix for every subsystem in this distributed recursive predictor has been shown to be equal to that of the well known kalman filter utilizing only local system output measurements which makes it possible to robustify this state predictor using a sensitivity penalization approach numerical simulation results illustrate that prediction accuracy of the suggested procedure may sometimes be as good as that of the lumped kalman filter