On the general problem of pole assignment

Given a linear, time-invariant, minimal and strictly proper system  set of monic polynomials φ _i (s), i = l, 2, [tdot],q, such that φ _i (s) divides φ _i?1 (s), i = 2, 3, [tdot],q a method for finding a proper feedback system  which makes the invariant polynomials of the closed-loop system equal to the φ _i (s) is established and a sufficient condition which ensures the existence of  is determined. This method can also be used to assign the poles of the compensated system provided that certain poles are multiple. The order of the required compensator is generally loss than that of the Luenberger or the Wolovich compensation schemes.     

An approximation method for high-order fractional derivatives of algebraically singular functions

The fractional derivative D^qf(s) (0≤s≤1) of a given function f(s) with a positive non-integer q is defined in terms of an indefinite integral. We propose a uniform approximation scheme to D^qf(s) for algebraically singular functions f(s)=s^αg(s) (α>−1) with smooth functions g(s). The present method consists of interpolating g(s) at sample points t_j in [0,1] by a finite sum of the Chebyshev polynomials. We demonstrate that for the non-negative integer m such that m<q<m+1, the use of high-order derivatives g⁽ⁱ⁾(0) and g⁽ⁱ⁾(1) (0≤i≤m) at both ends of [0,1] as well as g(t_j), t_j∈[0,1] in interpolating g(s), is essential to uniformly approximate D^q{s^αg(s)} for 0≤s≤1 when α≥q−m−1. Some numerical examples in the simplest case 1<q<2 are included.     

Adaptive refinement for convection-diffusion problems based on a defect-correction technique and finite difference method

A difference method is presented for singularly perturbed convection-diffusion problems with discretization error estimates of high order (orderp), which hold uniformly in the singular perturbation parameterε. The method is based on the use of a defect-correction technique and special adaptively graded and patched meshes, with meshsizes varying betweenh andε ^3/2 h whenp=2, whereh is the meshsize, used in the part of the domain where the solution is smooth, andε ^3/2 h is the final meshsize in the boundary layer. Similar constructions hold for interior layers. The correction operator is a monotone operator, enabling the estimate of the error of optimal order in maximum norm. The total number of meshpoints used in ad-dimensional problem isO(ε ^?s)h ^?d+O(h ^?d), wheres is 1/p or 1/2p, respectively in the case of boundary or interior layer.     

Blending two parametric curves

Segments of two given curves can be blended to produce a segment of a new curve. Blending can provide a smooth transition from one curve to another and can give various degrees of smoothness at the endpoints of the blend, where the smoothness is measured analogously to parametric continuity C⁽ⁿ⁾ and geometric continuity G⁽ⁿ⁾. Blending can provide an approximation to a given curve segment. The accuracy of the approximation to short segments obtained by different blending formulas is compared via asymptotic analysis. Finally, it is shown how to find a blend that is a parametric polynomial whose parameter is approximately an arc length parameter.     

An optimal visibility graph algorithm for triangulated simple polygons

LetP be a triangulated simple polygon withn sides. The visibility graph ofP has an edge between every pair of polygon vertices that can be connected by an open segment in the interior ofP. We describe an algorithm that finds the visibility graph ofP inO(m) time, wherem is the number of edges in the visibility graph. Becausem can be as small asO(n), the algorithm improves on the more general visibility algorithms of Asanoet al. [AAGHI] and Welzl [W], which take Θ(n ²) time, and on Suri'sO(m logn) visibility graph algorithm for simple polygons [S].     

The super connectivity of exchanged hypercubes

The exchanged hypercube EH(s,t) where s?1 and t?1 are two positive integers, proposed by Loh et al. [The exchanged hypercube, IEEE Transactions on Parallel and Distributed Systems 16 (9) (2005) 866-874], is obtained by systematically removing links from a binary hypercube Qn. This paper determines that the super connectivity and the super edge-connectivity of EH(s,t) are 2s where s?t. That is, for s?t, at least 2s vertices (resp. 2s edges) of EH(s,t) are removed to get a disconnected graph that contains no isolated vertex.     

Existence of solutions to singular integral equations

Nonnegative solutions are established for singular integral equations of the form y(t) = h(t) + ∫^T₀ k(t, s)f(s, y(s)) ds for t ∈ [0, T]. Here f may be singular at y = 0.     

Stable polyhedra in parameter space

A typical uncertainty structure of a characteristic polynomial is P(s)=A(s)Q(s)+B(s) with A(s) and B(s) fixed and Q(s) uncertain. In robust controller design Q(s) may be a controller numerator or denominator polynomial; an example is the PID controller with Q(s)=K_I+K_Ps+K_Ds². In robustness analysis Q(s) may describe a plant uncertainty. For fixed imaginary part of Q(jω), it is shown that Hurwitz stability boundaries in the parameter space of the even part of Q(jω) are hyperplanes and the stability regions are convex polyhedra. A dual result holds for fixed real part of Q(jω). Also σ-stability with the real parts of all roots of P(s) smaller than σ is treated.Under the above conditions, the roots of P(s) can cross the imaginary axis only at a finite number of discrete “singular” frequencies. Each singular frequency generates a hyperplane as stability boundary. An application is robust controller design by simultaneous stabilization of several representatives of A(s) and B(s) by a PID controller. Geometrically, the intersection of convex polygons must be calculated and represented tomographically for a grid on K_P.     

Classification of dynamic processes and PID controller tuning in a parameter plane

A quadruplet, defined by the ultimate frequency ω_u, the ultimate gain k_u, the angle φ of the tangent to the Nyquist curve at the ultimate frequency and the gain G_p(0), is sufficient for classification of a large class of stable processes, processes with oscillatory dynamics, integrating and unstable processes G_p(s). From the model defined by the above quadruplet, a two parameter model G_n(s_n) is obtained by the time and amplitude normalizations. Two parameters of G_n(s_n), the normalized gain ρ and the angle φ, are coordinates of the classification ρ-φ parameter plane. Model G_n(s_n) is used to obtain the desired closed-loop system performance/robustness tradeoff in the desired region of the classification plane. Tuning procedures and tuning formulae are derived guaranteeing almost the same performance/robustness tradeoff as obtained by the optimal PID controller, applied to G_p(s) classified to the same region of the classification plane. Validity of the proposed method is demonstrated on a test batch consisting of stable processes, processes with oscillatory dynamics, integrating and unstable processes, including dead-time.     

A discrete geometry approach for dominant point detection

We propose two fast methods for dominant point detection and polygonal representation of noisy and possibly disconnected curves based on a study of the decomposition of the curve into the sequence of maximal blurred segments [2]. Starting from results of discrete geometry [3] and [4], the notion of maximal blurred segment of width ν[2] has been proposed, well adapted to possibly noisy curves. The first method uses a fixed parameter that is the width of considered maximal blurred segments. The second method is deduced from the first one based on a multi-width approach to obtain a non-parametric method that uses no threshold for working with noisy curves. Comparisons with other methods in the literature prove the efficiency of our approach. Thanks to a recent result [5] concerning the construction of the sequence of maximal blurred segments, the complexity of the proposed methods is O(n log n). An application of vectorization is also given in this paper.     

Hexagon-based all-quadrilateral mesh generation with guaranteed angle bounds

In this paper, we present a novel hexagon-based mesh generation method which creates all-quadrilateral (all-quad) meshes with guaranteed angle bounds and feature preservation for arbitrary planar domains. Given any planar curves, an adaptive hexagon-tree structure is constructed by using the curvature of the boundaries and narrow regions. Then a buffer zone and a hexagonal core mesh are created by removing elements outside or around the boundary. To guarantee the mesh quality, boundary edges of the core mesh are adjusted to improve their formed angles facing the boundary, and two layers of quad elements are inserted in the buffer zone. For any curve with sharp features, a corresponding smooth curve is firstly constructed and meshed, and then another layer of elements is inserted to match the smooth curve with the original one. It is proved that for any planar smooth curve all the element angles are within [60° ? ε, 120° + ε] (ε ? 5°). We also prove that the scaled Jacobians defined by two edge vectors are in the range of [sin (60° ? ε),  sin 90°], or [0.82, 1.0]. The same angle range can be guaranteed for curves with sharp features, with the exception of small angles in the input curve. Furthermore, an approach is introduced to match the generated interior and exterior meshes with a relaxed angle range, [30°, 150°]. We have applied our algorithm to a set of complicated geometries, including the China map, the Lake Superior map, and a three-component air foil with sharp features. In addition, all the elements in the final mesh are grouped into five types, and most elements only need a few flops to construct the stiffness matrix for finite element analysis. This will significantly reduce the computational time and the required memory during the stiffness matrix construction.     

Scalable 2D Convex Hull and Triangulation Algorithms for Coarse Grained Multicomputers

In this paper we describe scalable parallel algorithms for building the convex hull and a triangulation ofncoplanar points. These algorithms are designed for thecoarse grained multicomputermodel:pprocessors withO(n/p)⪢O(1) local memory each, connected to some arbitrary interconnection network. They scale over a large range of values ofnandp, assuming only thatn⩾p^1+ε(ε>0) and require timeO((T_sequential/p)+T_s(n, p)), whereT_s(n, p) refers to the time of a global sort ofndata on approcessor machine. Furthermore, they involve only a constant number of global communication rounds. Since computing either 2D convex hull or triangulation requires timeT_sequential=Θ(n log n) these algorithms either run in optimal time,Θ((n log n)/p), or in sort time,T_s(n, p), for the interconnection network in question. These results become optimal whenT_sequential/pdominatesT_s(n, p) or for interconnection networks like the mesh for which optimal sorting algorithms exist.     

Recursive definitions and fixed-points on well-founded structures

An expression such as ∀x(P(x)↔?(P)), where P occurs in ?(P), does not always define P. When such an expression implicitly definesP, in the sense of Beth (1953) [1] and Padoa (1900) [13], we call it a recursive definition. In the Least Fixed-Point Logic (LFP), we have theories where interesting relations can be recursively defined (Ebbinghaus, 1995 [4], Libkin, 2004 [12]). We will show that for some sorts of recursive definitions there are explicit definitions on sufficiently strong theories of LFP. It is known that LFP, restricted to finite models, does not have Beth’s Definability Theorem (Gurevich, 1996 [7], Hodkinson, 1993 [8], Dawar, 1995 [3]). Beth’s Definability Theorem states that, if a relation is implicitly defined, then there is an explicit definition for it. We will also give a proof that Beth’s Definability Theorem fails for LFP without this finite model restriction. We will investigate fragments of LFP for which Beth’s Definability Theorem holds, specifically theories whose models are well-founded structures.     

Coefficients for studying one-step rational schemes for IVPs in ODEs: I

In [1,2], we considered an approach of global formulation of one-step integrators of arbitrary order on a self-adjusting rational approximant by introducing the constants C^(s)_j, s = 1, 2, 3, …, j = 2, 3, …, j − s ≥ 1. In the present consideration, we motivate a study of this approach to derive a class of one-step methods of variable order and variable stepsize.     

On decoupling the H-optimal sensitivity problem for products of plants

In this note we show how to solve the H^∞-optimal sensitivity problem for a SISO plant P(s) = P₁(s)P₂(s), given the solutions for P₁(s), P₂(s). This allows us to solve the problem for systems of the form e^−hsP₀(s), where P₀(s) is the transfer function of a stable, LTI, finite dimensional system.     

Double solutions of boundary value problems for 2mth-order differential equations and difference equations

A double fixed-point theorem is applied to obtain the existence of at least two positive solutions for the boundary value problem, (−1)^my^(2m)(t) = f(y(t)), t ϵ [0, 1], y⁽²ⁱ⁾(0) = y⁽²ⁱ⁺¹⁾(1) = 0, 0 ≤ i ≤ m−1. It is later applied to obtain the existence of at least two positive solutions for the analogous discrete boundary value problem, (−1)^mΔ^2mu(k) = g(u(k)), k ϵ {0, …, N}, Δ²ⁱu(0) = Δ²ⁱ⁺¹u(N + 1) = 0, 0 ⩽ m − 1.     

On simplifying assumptions of Runge-Kutta methods for index 2 differential algebraic problems

In this paper we show a result that ensures certain order for the local error Runge-Kutta methods for index 2 differential algebraic problems with the help of the simplifying conditionsB(p),C(q),D(r) andA ₁(s) for the differential component andB(p), C(q), andA ₂(s) for the algebraic component.     

ANN-based GA for generating the sizing curve of stand-alone photovoltaic systems

Recent advances in artificial intelligence techniques have allowed the application of such technologies in real engineering problems. In this paper, an artificial neural network-based genetic algorithm (ANN-GA) model was developed for generating the sizing curve of stand-alone photovoltaic (SAPV) systems. Due to the high computing time needed for generating the sizing curves and complex architecture of the neural networks, the genetic algorithm is used in order to find the optimal architecture of the ANN (number of hidden layers and the number of neurons within each hidden layer). Firstly, a numerical method is used for generating the sizing curves for different loss of load probability (LLP) corresponding to 40 sites located in Algeria. The inputs of ANN-GA are the geographical coordinates and the LLP while the output is the sizing curve represented by C_A = f(C_S) (i.e., 30-points were taken from each sizing curve). Subsequently, the proposed ANN-GA model has been trained by using a set of 36 sites, whereas data for 4 sites (randomly selected) which are not included in the training dataset have been used for testing the ANN-GA model. The results obtained are compared and tested with those of the numerical method in order to show the effectiveness of the proposed approach.     

A numerical method to minimize resource consumption by linear systems with constant delay

A numerical method to minimize the resource consumption by the linear systems with constant time delay in the system phase states was proposed. Its global convergence to the ?-optimal solution was proved. By the ?-optimal solution is meant the feasible control u(t), t ∈ [0, T], driving the system to the ?-neighborhood of the origin and providing a value of the functional that differs from the optimal one at most by ?.     

The RKHS method for numerical treatment for integrodifferential algebraic systems of temporal two-point BVPs

Many problems arising in different fields of sciences and engineering can be reduced, by applying some appropriate discretization, either to a system of integrodifferential algebraic equations or to a sequence of such systems. The aim of the present analysis is to implement a relatively recent computational method, reproducing kernel Hilbert space, for obtaining the solutions of integrodifferential algebraic systems of temporal two-point boundary value problems. Two extended inner product spaces W[0, 1] and H[0, 1] are constructed in which the boundary conditions of the systems are satisfied, while two smooth kernel functions R _t (s) and r _t (s) are used throughout the evolution of the algorithm in order to obtain the required grid points. An efficient construction is given to obtain the numerical solutions for the systems together with an existence proof of the exact solutions based upon the reproducing kernel theory. In this approach, computational results of some numerical examples are presented to illustrate the viability, simplicity, and applicability of the algorithm developed.