Small-time local controllability and continuity of the optimal time function for linear systems

For a finite-dimensional linear system, in which the control is restricted to belong to a completely arbitrary setJ, we give a simple necessary and sufficient condition for small-time local controllability from a pointp. The condition is equivalent to a characterization of the property that the Bellman function for the corresponding minimum-time optimal control problem is continuous atp.This work was partially supported by the National Science Foundation, Grant No. MCS-78-02442.     

On the Attainable Sets of Control Systems with p-Integrable Controls

It is well known that, for a control system, under suitable assumptions, the closure of the attainable set does not change if we consider p-integrable controls for different p. This is an interesting problem and has not been studied in depth, whether or not the attainable set changes when p changes. We show that, for a linear system, the attainable sets may be different for different p. In the two-dimensional case, we prove that the number of indices for which the attainable sets change is finite. Moreover, we show that, for a class of systems, the attainable sets are the same, when the time duration is large enough.     

General Linear Quadratic Optimal Stochastic Control Problem Driven by a Brownian Motion and a Poisson Random Martingale Measure with Random Coefficients

In this article, we consider a linear-quadratic optimal control problem (LQ problem) for a controlled linear stochastic differential equation driven by a multidimensional Browinan motion and a Poisson random martingale measure in the general case, where the coefficients are allowed to be predictable processes or random matrices. By the duality technique, the dual characterization of the optimal control is derived by the optimality system (so-called stochastic Hamilton system), which turns out to be a linear fully coupled forward-backward stochastic differential equation with jumps. Using a decoupling technique, the connection between the stochastic Hamilton system and the associated Riccati equation is established. As a result, the state feedback representation is obtained for the optimal control. As the coefficients for the LQ problem are random, here, the associated Riccati equation is a highly nonlinear backward stochastic differential equation (BSDE) with jumps, where the generator depends on the unknown variables K, L, and H in a quadratic way (see (5.9) herein). For the case where the generator is bounded and is linearly dependent on the unknown martingale terms L and H, the existence and uniqueness of the solution for the associated Riccati equation are established by Bellman's principle of quasi-linearization.     

Inverse <Emphasis Type="Italic">p</Emphasis>-median problems with variable edge lengths

The inverse p-median problem with variable edge lengths on graphs is to modify the edge lengths at minimum total cost with respect to given modification bounds such that a prespecified set of p vertices becomes a p-median with respect to the new edge lengths. The problem is shown to be strongly NP{\mathcal{NP}}-hard on general graphs and weakly NP{\mathcal{NP}}-hard on series-parallel graphs. Therefore, the special case on a tree is considered: It is shown that the inverse 2-median problem with variable edge lengths on trees is solvable in polynomial time. For the special case of a star graph we suggest a linear time algorithm.     

Solutions and multiple solutions for problems with the <Emphasis Type="Italic">p</Emphasis>-Laplacian

In this paper we consider two nonlinear elliptic problems driven by the p-Laplacian and having a nonsmooth potential (hemivariational inequalities). The first is an eigenvalue problem and we prove that if the parameter λ < λ₂ = the second eigenvalue of the p-Laplacian, then there exists a nontrivial smooth solution. The second problem is resonant both near zero and near infinity for the principal eigenvalue of the p-Laplacian. For this problem we prove a multiplicity result. Our approach is variational based on the nonsmooth critical point theory. Second author is Corresponding author.     

Boundedness of Convolution Operators and Input–Output Maps between Weighted Spaces

We ask when convolution operators with scalar- or operator-valued kernel functions map between weighted L² spaces of Hilbert space-valued functions. For a certain class of decreasing weights, including negative powers (t + a)^−m for example, we solve the one-weight problem completely by using Laplace transforms and Bergman-type spaces of vector-valued analytic functions. For a much more general class of decreasing weights, we solve the one-weight problem for all positive real kernels (also for L^p(w) with p > 1), by results on Steklov operators which generalise the weighted Hardy inequality. When the kernel function is a strongly continuous semigroup of bounded linear Hilbert space operators, which arises from input–output maps of certain linear systems, then the most obvious sufficient condition for boundedness, obtained by taking norm signs inside the integrals, is also necessary in many cases, but not in general. Submitted: July 15, 2007.,Revised: November 19, 2007.,Accepted: December 14, 2007.     

Mean-field stochastic control with elephant memory in finite and infinite time horizon

ABSTRACT

Our purpose of this paper is to study stochastic control problems for systems driven by mean-field stochastic differential equations with elephant memory, in the sense that the system (like the elephants) never forgets its history. We study both the finite horizon case and the infinite time horizon case.

• In the finite horizon case, results about existence and uniqueness of solutions of such a system are given. Moreover, we prove sufficient as well as necessary stochastic maximum principles for the optimal control of such systems. We apply our results to solve a mean-field linear quadratic control problem.

• For infinite horizon, we derive sufficient and necessary maximum principles.

  As an illustration, we solve an optimal consumption problem from a cash flow modelled by an elephant memory mean-field system.

     

Problems of Linear Discrete Games of Pursuit

In this paper, we consider two problems of linear discrete games of pursuit. In each of them, the terms of the sequence defining the pursuer’s control are bounded by some positive number. In the first problem, the terms of the sequence defining the quarry’s control are bounded by some positive number and, in the second problem, the sum of the pth powers of the terms of this sequence is bounded by a given number. For each problem, we obtain a necessary and sufficient condition for the termination of pursuit from all points in space.__________Translated from Matematicheskie Zametki, vol. 77, no. 5, 2005, pp. 707–718.Original Russian Text Copyright ©2005 by G. I. Ibragimov.     

Parametrization of central Frattini extensions and isomorphisms of small group rings

We solve the modular isomorphism problem for small group rings, i.e., we determine, for a given finite p-group H, precisely which central Frattini extensions of H give rise to isomorphic small group rings over the field with p elements. The first author acknowledges support by the Deutsche Forschungsgemeinschaft.     

Well-posed solvability of an analytic Cauchy problem in spaces with an integral metric

We study the complex Cauchy problem for a system of linear differential equations in a class of analytic functions with an integral metric. For the case in which L_p is a weighted Lebesgue space, we obtain necessary and sufficient conditions for the local solvability of the problem.     

Average case complexity of linear multivariate problems I. Theory

We study the average case complexity of linear multivariate problems, that is, the approximation of continuous linear operators on functions of d variables. The function spaces are equipped with Gaussian measures. We consider two classes of information. The first class Λ^std consists of function values, and the second class Λ^all consists of all continuous linear functionals. Tractability of a linear multivariate problem means that the average case complexity of computing an ε-approximation is O((1/)^p) with p independent of d. The smallest such p is called the exponent of the problem. Under mild assumptions, we prove that tractability in Λ^all is equivalent to tractability in Λ^std and that the difference of the exponents is at most 2. The proof of this result is not constructive. We provide a simple condition to check tractability in Λ^all. We also address the issue of how to construct optimal (or nearly optimal) sample points for linear multivariate problems. We use relations between average case and worst case settings. These relations reduce the study of the average case to the worst case for a different class of functions. In this way we show how optimal sample points from the worst case setting can be used in the average case. In Part II we shall apply the theoretical results to obtain optimal or almost optimal sample points, optimal algorithms, and average case complexity functions for linear multivariate problems equipped with the folded Wiener sheet measure. Of particular interest will be the multivariate function approximation problem.     

Minimum-order functional observers

The article considers the construction of a minimum-order observer for a linear state functional of a linear dynamical system. For a one-output system we derive a necessary and sufficient condition that allows reconstruction of the functional by a k th order observer. This result is generalized to a system with vector output. An algorithm for the construction of a minimal observer is proposed. The problem is solved by the method of decomposition into scalar observers.     

The vector-valued Wiener-Hopf equation for a mixed boundary-value problem of diffraction at a wedge intersected by a half-plane

For a mixed boundary-value problem in a nonregular region we obtain the vector-valued Wiener-Hopf equation, which is then reduced to infinite systems of linear algebraic equations using the factorization method and Liouville's theorem. It then becomes possible to solve the equation with prescribed precision for arbitrary values of the parameters of the problem. In the stationary case the solution is obtained in closed form.Translated fromMatematichni Metodi ta Fiziko-Mechanichni Polya, Vol. 40, No. 3, 1997, pp. 87–92.     

Local well‐posedness for a system of quadratic nonlinear Schrödinger equations in one or two dimensions

In this article, the local well‐posedness of Cauchy's problem is explored for a system of quadratic nonlinear Schrödinger equations in the space L^p( R ⁿ). In a special case of mass resonant 2 × 2 system, it is well known that this problem is well posed in H^s(s≥0) and ill posed in H^s(s < 0) in two‐space dimensions. By translation on a linear semigroup, we show that the general system becomes locally well posed in L^p( R ²) for 1 < p < 2, for which p can arbitrarily be close to the scaling limit p_c=1. In one‐dimensional case, we show that the problem is locally well posed in L¹( R ); moreover, it has a measure valued solution if the initial data are a Dirac function. Copyright © 2016 John Wiley & Sons, Ltd.     

Dinkelbach Approach to Solving a Class of Fractional Optimal Control Problems

We consider optimal control problems with functional given by the ratio of two integrals (fractional optimal control problems). In particular, we focus on a special case with affine integrands and linear dynamics with respect to state and control. Since the standard optimal control theory cannot be used directly to solve a problem of this kind, we apply Dinkelbach’s approach to linearize it. Indeed, the fractional optimal control problem can be transformed into an equivalent monoparametric family {P_q} of linear optimal control problems. The special structure of the class of problems considered allows solving the fractional problem either explicitly or requiring straightforward classical numerical techniques to solve a single equation. An application to advertising efficiency maximization is presented. This work was partially supported by the Università Ca’ Foscari, Venezia, Italy, the MIUR (PRIN cofinancing 2005), the Council for Grants (under RF President) and State Aid to Fundamental Science Schools (Grant NSh-4113.2008.6). We thank Angelo Miele, Panos Pardalos and the anonymous referees for comments and suggestions.     

Determination of a control function in three‐dimensional parabolic equations by Legendre pseudospectral method

A Legendre pseudospectral method is proposed for solving approximately an inverse problem of determining an unknown control parameter p(t) which is the coefficient of the solution u(x, y, z, t) in a diffusion equation in a three‐dimensional region. The diffusion equation is to be solved subject to suitably prescribed initial‐boundary conditions. The presence of the unknown coefficient p(t) requires an extra condition. This extra condition considered as the integral overspecification over the spacial domain. For discretizing the problem, after homogenization of the boundary conditions, we apply the Legendre pseudospectral method in a matrix based manner. As a results a system of nonlinear differential algebraic equations is generated. Then by using suitable transformation, the problem will be converted to a homogeneous time varying system of linear ordinary differential equations. Also a pseudospectral method for efficient solving of the resulted system of ordinary differential equations is proposed. The solution of this system gives the approximation to values of u and p. The matrix based structure of the present method makes it easy to implement. Numerical experiments are presented to demonstrate the accuracy and the efficiency of the proposed computational procedure. © 2010 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 28: 74‐93, 2012     

An H2-Type Norm of a Discrete-Time Linear Stochastic System with Periodic Coefficients Simultaneously Affected by an Infinite Markov Chain and Multiplicative White Noise Perturbations

This article investigates the problem of the definition and computation of an H₂-type norm for discrete-time time-varying periodic stochastic linear systems simultaneously affected by multiplicative white noise perturbations and random jumping according to a Markov chain with an infinite countable number of states. Also, we solve an optimization problem that contains, as a special case, the H₂ optimal control problem for the considered class of stochastic systems under the assumption of perfect state measurements.     

Book review of advances in gabor analysis,applied and numerical harmonic analysis,Hans G. Feichtinger and Thomas Strohmer (Eds.), Birkhäuser,Boston-Basel-Berlin, 2002, 356 pages. ISBN 0-8176-4239-0

In some recent publications it was shown that certain stationary stochastic dynamic programming problems with general state and action spaces can be solved by generalized linear programming. It Is the main aim of the present paper to demonstrate that a similar linear programming approach is feasible even in the non-stationary case. For this end, we formulate a programming problem (D^?) and show that (D^?) is equivalent to the problem of finding a p=optimal policy for the stochastic dynamic program, whereas a modification of (D^?) turns out to be the dual program of a pair of general linear programs.     

Equivalence of Minimal ?0- and ?p-Norm Solutions of Linear Equalities, Inequalities and Linear Programs for Sufficiently Small p

For a bounded system of linear equalities and inequalities, we show that the NP-hard ℓ ₀-norm minimization problem is completely equivalent to the concave ℓ _p -norm minimization problem, for a sufficiently small p. A local solution to the latter problem can be easily obtained by solving a provably finite number of linear programs. Computational results frequently leading to a global solution of the ℓ ₀-minimization problem and often producing sparser solutions than the corresponding ℓ ₁-solution are given. A similar approach applies to finding minimal ℓ ₀-solutions of linear programs.     

A linear boundary value problem for weakly quasiregular mappings in space

Given a number a weakly L-quasiregular map on a domain in space is a map u in a Sobolev space that satisfies almost everywhere in In this paper, we study the problem concerning linear boundary values of weakly L-quasiregular mappings in space with dimension It turns out this problem depends on the power p of the underlying Sobolev space. For p not too far below the dimension n we show that a weakly quasiregular map in can only assume a quasiregular linear boundary value; however, for all and , we prove a rather surprising existence result that every linear map can be the boundary value of a weakly L-quasiregular map in Received July 20, 2000 / Accepted September 22, 2000 / Published online December 8, 2000