Stochastic adaptive pole-zero assignment with convergence analysis

The adaptive control u_n is designed for the stochastic system A(z)y_n+1 = B(z)u_n+C(z)w_n+1 with unknown constant matrix coefficients in the polynomials A(z), B(z) and C(z) in the shift-back operator with the purposes that (1) the unknown matrices are strongly consistently estimated and (2) the poles and zeros are replaced in such a way that the system itself is transferred to A⁰(z)y_n+1 = B⁰(z)u_n⁰+_n+1 with given A⁰(z), B⁰(z) and u_n⁰ so that the pole-zero assignment error {_n+1} is minimized. The problem of adaptive pole-zero assignment combined with tracking is also considered in this paper. Conditions used are imposed only on A(z), B(z) and C(z).     

Adaptive robust control of nonholonomic systems with stochastic disturbances

Based on the Brockett’s necessary condition for feedback asymptotic stabilization[1], nonholonomic systems fail to be stabilized at the origin by any static continuous state feedback though they are open loop controllable. There are two novel approaches …     

Optimum Control of a Certain Class of Servomechanism†

Linear control systems governed by the vector matrix differential equation x = A x + B u have been considered. It has been shown how to find the optimum control u so that the system, starting from an initial position x(0), is steered to a state specifying the first p coordinates of the system in time t _o fixed in advance, the values attained by the (n—p) coordinates being immaterial, where n is the dimension of the system. The optimization considered here is with regard to the norm of u supposed to belong to L _m E _r space.     

On Word Equations in One Variable

For a word equation E of length n in one variable x occurring # _x times in E a resolution algorithm of O(n+# _x log n) time complexity is presented here. This is the best result known and for the equations that feature #_x < \fracnlogn\#_{x}<\frac{n}{\log n} it yields time complexity of O(n) which is optimal. Additionally it is proven here that the set of solutions of any one-variable word equation is either of the form F or of the form F∪(uv)⁺ u where F is a set of O(log n) words and u, v are some words such that uv is a primitive word.     

Three point discretization of order four and six for (du :dx) of the solution of non-linear singular two point boundary value problem

We present finite difference methods of order four and six for the numerical solution of (du/dx) for the non-linear differential equation u″ = f(x,u,u′), 0 < x > 1 subject to the boundary conditions u(0) = A, u(l) =B. The proposed methods require only three grid points and applicable to both singular and non-singular problems. Numerical examples are given to illustrate the methods and their convergence.     

Two-sided bounds for the asymptotic behaviour of free nonlinear vibration systems with application of the differential calculus of norms

This paper deals with the free nonlinear dynamical system [xdot](t)=A x(t)+h(t, x(t)), t≥t ₀, x(t ₀)=x ₀, where A is an n×n-matrix and h a nonlinear vector function with h(t, u)=o(∥u∥). As the first novel point, a lower bound for the asymptotic behaviour on the solution x(t) is derived. Two methods are applied to determine the optimal two-sided bounds, where one of the methods is the differential calculus of norms. In this context, the second novel point enters; it consists of a new strategy to significantly reduce the computation time for the determination of the optimal constants in the two-sided bounds. The obtained results are especially of interest in engineering and cannot be obtained by the methods used so far.     

On the fuzzy difference equation xn+1 = A+B/xn

 In this paper we study the existence the oscillatory behavior the boundedness and the asymptotic behavior of the positive solutions of the fuzzy equation x _n+1 =A+B/x _n ,n=0,1,… where x _n is a sequence of fuzzy numbers, A, B are fuzzy numbers.     

On the possibility of using complex values in fuzzy logic for representing inconsistencies

In science and engineering, there are “paradoxical” cases in which we have some arguments in favor of some statement A (so the degree to which A is known to be true is positive (nonzero)), and we have some arguments in favor of its negation ¬A, and we do not have enough information to tell which of these two statements is correct. Traditional fuzzy logic, in which “truth values” are described by numbers from the interval [0, 1], easily describes such “paradoxical” situations: the degree a to which the statement A is true and the degree 1−a to which its negation ¬A is true can both be positive. In this case, if we use traditional fuzzy &-operations (min or product), the “truth value” a&(1−a) of the statement A&¬A is positive, indicating that there is some degree of inconsistency in the initial beliefs. When we try to use fuzzy logic to formalize expert reasoning in the humanities, we encounter the problem that is humanities, in addition to the above-described paradoxical situations caused by the incompleteness of our knowledge, there are also true paradoxes, i.e., statements that are perceived as true and false at the same time. For such statements, A&¬A=“true.” The corresponding equality a&(1−a)=1 is impossible in traditional fuzzy logic (where a&(1−a) is always≤0.5), so, to formalize such true paradoxes, we must extend the set of truth values from the interval [0, 1]. In this paper we show that such an extension can be achieved if we allow truth values to be complex numbers. © 1998 John Wiley & Sons, Inc.     

Solving the forced Duffing equation with integral boundary conditions in the reproducing kernel space

In this paper, we propose a new method to solve the forced Duffing equation with integral boundary conditions. Its exact solution is represented in the form of a series in the reproducing kernel space. The n-term approximation u _n (x) of the exact solution u(x) is proved to converge to the exact solution. Some numerical examples are displayed to demonstrate the accuracy of the present method.     

Backstepping boundary control of Burgers’ equation with actuator dynamics

In this paper, we propose a backstepping boundary control law for Burgers’ equation with actuator dynamics. While the control law without actuator dynamics depends only on the signals u(0,t) and u(1,t), the backstepping control also depends on u_x(0,t), u_x(1,t), u_xx(0,t) and u_xx(1,t), making the regularity of the control inputs the key technical issue of the paper. With elaborate Lyapunov analysis, we prove that all these signals are sufficiently regular and the closed-loop system, including the boundary dynamics, is globally H³ stable and well posed.     

Fault diagnosis in loop-connected systems

The paper considers fault diagnosis in a large system comprising a collection of small subsystems or units which can test one another for the existence of a faulty condition. If subsystem α is not faulty and tests subsystem β, a correct indication of the status of β is obtained; if α is faulty, the test outcome contains meaningless information. A particular form of interconnection is examined. For a system with n units u_o,u₁,…,u_{n ? 1}, for each i unit u_i tests u_{i + 1},u_{i + 2},…,u_{i + A} (modulo n arithmetic being understood), where A is a preselected integer. If t is the maximum number of faulty units, we show that when t ? A, all faults are immediately diagnosable if n ? 2t + 1; we also show that when t ? A, at least A faults can be diagnosed if and only if n ? s(t ? As) + t + A + 1, where s is the integer which maximizes the quadratic function f(x) = x(t ? Ax) of the integer variable x.     

Computing median and antimedian sets in median graphs

The median (antimedian) set of a profile π=(u ₁,…,u _k ) of vertices of a graph G is the set of vertices x that minimize (maximize) the remoteness ∑ _i d(x,u _i ). Two algorithms for median graphs G of complexity O(n idim(G)) are designed, where n is the order and idim(G) the isometric dimension of G. The first algorithm computes median sets of profiles and will be in practice often faster than the other algorithm which in addition computes antimedian sets and remoteness functions and works in all partial cubes.     

Substitutions into propositional tautologies

We prove that there is a polynomial time substitution (y₁,…,yn):=g(x₁,…,xk) with k?n such that whenever the substitution instance A(g(x₁,…,xk)) of a 3DNF formula A(y₁,…,yn) has a short resolution proof it follows that A(y₁,…,yn) is a tautology. The qualification “short” depends on the parameters k and n.     

Sufficient conditions for the existence and asymptotic behaviour of solution to a quasi-linear elliptic problem

In this article, we combine the existing regularity theory, perturbation method and the lower and upper solutions method to study the existence and asymptotic behaviour of positive solution to a boundary value problem for the p-Laplacian operator. More exactly, we study the existence and asymptotic behaviour of the positive solution to a quasi-linear elliptic problem of the form?Δ _p u=λ a(x)g(u) in D′(Ω), u>0 in Ω, lim _{x→? Ω} u(x)=0. Under some conditions on a and g, we show that there is a non-negative number Λ₀ such that for all λ∈(0, Λ₀], the problem has a solution u _λ in the sense of distribution, which is bounded from above by some positive numbers μ(λ). Such estimates and the asymptotic behaviour are important in computer programs when we know an algorithm for determining the solution.     

Calculus of fuzzy hierarchical censored production rules (FHCPRs)

The article addresses the problem of reasoning under time constraints with incomplete, vague, and uncertain information. It is based on the idea of Variable Precision Logic (VPL), introduced by Michalski and Winston, which deals with both the problem of reasoning with incomplete information subject to time constraints and the problem of reasoning efficiently with exceptions. It offers mechanisms for handling trade-offs between the precision of inferences and the computational efficiency of deriving them. As an extension of Censored Production Rules (CPRs) that exhibit variable precision in which certainty varies while specificity stays constant, a Hierarchical Censored Production Rules (HCPRs) system of Knowledge Representation proposed by Bharadwaj and Jain exhibits both variable certainty as well as variable specificity. Fuzzy Censored Production Rules (FCPRs) are obtained by augmenting ordinary fuzzy conditional statement: “if X is A then Y is B” (or A(x) ⇒ B(y) for short) with an exception condition and are written in the form: “if X is A then Y is B unless Z is C” (or A(x) ⇒ B(y) ∥ C(z)). Such rules are employed in situations in which the fuzzy conditional statement “if X is A then Y is B” holds frequently and the exception condition “Z is C” holds rarely. Thus, using a rule of this type we are free to ignore the exception condition, when the resources needed to establish its presence are tight or there simply is no information available as to whether it holds or does not hold. Thus if … then part of the FCPR expresses important information while the unless part acts only as a switch that changes the polarity of “Y is B” to “Y is not B” when the assertion “Z is C” holds. Our aim is to show how an ordinary fuzzy production rule on suitable modifications and augmentation with relevant information becomes a Fuzzy Hierarchical Censored Production Rules (FHCPRs), which in turn enables to resolve many of the problems associated with usual fuzzy production rules system. Examples are given to demonstrate the behavior of the proposed schemes. © 1996 John Wiley & Sons, Inc.     

Monotone properties of certain classes of solutions of second-order difference equations

The authors consider the difference equations

δ(a_nδx_n)=q_nx_n+1

and

δ(a_nδx_n)=q_nf(x_n+1),

where a_n > 0, q_n > 0, and f: R å R is continuous with uf(u) > 0 for u ≠ 0. They obtain necessary and sufficient conditions for the asymptotic behavior of certain types of nonoscillatory solutions of (*) and sufficient conditions for the asymptotic behavior of certain types of nonoscillatory solutions of (**). Sufficient conditions for the existence of these types of nonoscillatory solutions are also presented. Some examples illustrating the results and suggestions for further research are included.     

On weighted P‐quantile aggregation

We consider the problem of aggregating ordinal information with quantitative or qualitative importance based on quantile operations. For a bag 〈x₁, x₂, …, x_n〉 in real or in (finite) ordinal scales, the quantile operations used in this paper are operating based on the floating position index of x_i that is determined by its position on the ordered sequence (x₍₁₎, x₍₂₎, …, x_(n)), where x_(i) is the ith smallest element of the bag 〈x₁, x₂, …, x_n〉. We call this type of quantile aggregation as the floating position index‐based quantile (p‐quantile) aggregation. We study on weighted p‐quantile aggregation in real scales and extend the corresponding techniques to p‐quantile aggregation of ordinal information with quantitative importance. The aggregated result of the latter is represented by a general ordinal proportional 2‐tuple. On basis of the notion of importance transformation (that is modified from Yager), we investigate p‐quantile aggregation of ordinal information with qualitative importance. Then, we use p‐quantile aggregation to define the floating position index‐based ordered weighted averaging (P‐OWA) aggregation of ordinal information with qualitative importance and apply it to the problem of multicriteria decision making. © 2008 Wiley Periodicals, Inc.     

Inversion Problems in theq-Hahn Tableau

If { P_n(x;q)}_nis a family of polynomials belonging to the q -Hahn tableau then each polynomial of this family can be written as P_n(x;q) = ∑_{m = 0}ⁿD_m(n)_m(x) where _m(x) stands for (x;q)_mor x^m. In this paper we solve the corresponding inversion problem, i.e. we find the explicit expression for the coefficients I_m(n) in the expansion _n(x) = ∑_{m = 0}ⁿI_m(n)P_m(x;q).     

Processing fuzzy set membership functionals as vectors

A framework is presented for processing fuzzy sets for which the universe of discourse X = {x} is a separable Hilbert Space, which, in particular, may be a Euclidian Space. In a given application, X would constitute a feature space. The membership functions of sets in such X are then “membership functionals”, that is, mappings from a vector space to the real line. This paper considers the class Φ of fuzzy sets A, the membership functionals μ _A of which belong to a Reproducing Kernel Hilbert Space (RKHS) F(X) of bounded analytic functionals on X, and satisfy the constraint . These functionals can be expanded in abstract power series in x, commonly known as Volterra functional series in x. Because of the one-to-one relationship between the fuzzy sets A and their respective μ _A , one can process the sets A as objects using their μ _A as intermediaries. Thus the structure of the uncertainty present in the fuzzy sets can be processed in a vector space without descending to the level of processing of vectors in the feature space as usually done in the literature in the field. Also, the framework allows one to integrate human and machine judgments in the definition of fuzzy sets; and to use concepts analogous to probabilistic concepts in assigning membership values to combinations of fuzzy sets. Some analytical and interpretive consequences of this approach are presented and discussed. A result of particular interest is the best approximation of a membership functional μ _A in F(X) based on interpolation on a training set {(v ⁱ , u ⁱ ),i = 1, . . . , q} and under the positivity constraint. The optimal analytical solution comes out in the form of an Optimal Interpolative Neural Network (OINN) proposed by the author in 1990 for best approximation of pattern classification systems in a F(X) space setting. An example is briefly described of an application of this approach to the diagnosis of Alzheimer’s disease.