The linear quadratic minimum-time problem for a class of discrete systems

We consider a linear discrete-time systems controlled by inputs on L ²([0, t _N ], U), where (t _i )_{1?≤?i?≤?N} is a given sequence of times. The final time t _N (or N) is considered to be free. Given an initial state x ₀ and a final one x _d , we investigate the optimal control which steers the system from x ₀ to x _d with a minimal cost J(N, u) that includes the final time and energy terms. We treat this problem for both infinte and finite dimensional state space. We use a method similar to the Hilbert Uniqueness Method. A numerical simulation is given.     

A simultaneous approach to inverse source problem by Green's function

In this paper, we consider an inverse source problem of identification of F(t) function in the linear parabolic equation u_t = u_xx + F(t) and u₀(x) function as the initial condition from the measured final data and local boundary data. Based on the optimal control framework by Green's function, we construct Fréchet derivative of Tikhonov functional. The stability of the minimizer is established from the necessary condition. The CG algorithm based on the Fréchet derivative is applied to the inverse problem, and results are presented for a test example. Copyright © 2014 John Wiley & Sons, Ltd.     

Simplified Generalized Gauss-Newton Iterative Method under Morozove Type Stopping Rule

Recently, Mahale and Nair considered a simplified generalized Gauss-Newton iterative method for getting an approximate solution for the nonlinear ill-posed operator equation under the modified general source condition. The advantage of this method and the source condition over the classical Gauss-Newton iterative method is that the iterations and source condition involve calculation of the Fréchet derivative only at the point x ₀, i.e., at the initial approximation for the exact solution x ^? of the nonlinear ill-posed operator equation F(x) = y. Motivated by the work of Qinian Jin and Tautenhan, error analysis of the simplified Gauss-Newton iterative method is done in this article under a Morozove-type stopping rule, which is much simpler than the stopping rule considered in the article of Mahale and Nair. An order optimal error estimate is obtained under a modified general source condition which also involves calculation of the Fréchet derivative at the point x ₀.     

Existence of solutions for a class of nonlinear control problems

We consider problems of control and problems of optimal control, monitored by an abstract equation of the formEx=N _u x in a finite interval [0,T]; here,x is the state variable with values in a reflexive Banach space;u is the control variable with values in a metric space;E is linear and monotone; andN _u is nonlinear of the Nemitsky type. Thus, by well-known devices, the results apply also to parabolic partial differential equations in a cylinder [0,T]×G,G ⁿ , with Cauchy data fort=0 and Dirichlet or Neumann conditions on the lateral surface of the cylinder. We prove existence theorems for solutions and existence theorems for optimal solutions, by reduction to a theorem of Kemochi for reflexive Banach spaces.     

On the determination of the impulsive Sturm–Liouville operator with the eigenparameter-dependent boundary conditions

In the present work, we consider the inverse problem for the impulsive Sturm–Liouville equations with eigenparameter-dependent boundary conditions on the whole interval (0,π) from interior spectral data. We prove two uniqueness theorems on the potential q(x) and boundary conditions for the interior inverse problem, and using the Weyl function technique, we show that if coefficients of the first boundary condition, that is, h₁,h₂, are known, then the potential function q(x) and coefficients of the second boundary condition, that is, H₁,H₂, are uniquely determined by information about the eigenfunctions at the midpoint of the interval and one spectrum or partial information on the eigenfunctions at some internal points and some of two spectra.     

Asymptotic behavior of the solutions of certain parabolic equations

Some laws in physics describe the change of a flux and are represented by parabolic equations of the form (*) \documentclass{article}\pagestyle{empty}\begin{document}$$\frac{{\partial u}}{{\partial t}}=\frac{\partial}{{\partial x_j }}(\eta \frac{{\partial u}}{{ax_j}}-vju),$$\end{document} j≤m, where η and v_j are functions of both space and time. We show under quite general assumptions that the solutions of equation (*) with homogeneous Dirichlet boundary conditions and initial condition u(x, 0) = u_o(x) satisfy The decay rate d > 0 only depends on bounds for η, v and G § R^m the spatial domain, while the constant c depends additionally on which norm is considered. For the solutions of equation (*) with homogeneous Neumann boundary conditions and initial condition u₀(x) ≥ 0 we derive bounds d₁u₁ ≤ u(x, t) ≤ d₂u₂, Where d_i, i = 1, 2, depend on bounds for η, v and G, and the u_i are bounds on the initial condition u₀.     

Modified quasilinearization and optimal initial choice of the multipliers part 1—Mathematical programming problems

In this paper, the problem of extremizing a functionf(x) subject to the constraint (x)=0 is considered. Here,f is a scalar,x ann-vector, and aq-vector. A modified quasilinearization algorithm is developed; its main property is a descent property in the performance indexR, the cumulative error in the constraint and the optimum condition.Modified quasilinearization differs from ordinary quasilinearization because of the inclusion of a scaling factor (or stepsize) in the system of variations. The stepsize is determined by a one-dimensional search so as to ensure the decrease in the performance indexR; this can be achieved through a bisection process starting from =1. Convergence is achieved whenR becomes smaller than some preselected value.In order to start the algorithm, some nominal values for the variablex and the multiplier must be chosen. In a real problem, the selection ofx can be made on the basis of physical considerations. Concerning , no useful guideline has been available thus far. In this paper, a method for selecting optimally is presented: the performance indexR is minimized with respect to . SinceR is a quadratic function of , the optimal initial multiplier is governed by a linear algebraic equation.Two numerical examples are presented, and it is shown that, if the initial multiplier is chosen optimally, modified quasilinearization converges to the solution. On the other hand, if the initial multiplier is chosen arbitrarily, modified quasilinearization may or may not converge to the solution. From the examples, it is concluded that the beneficial effect associated with the optimal initial choice of the multiplier lies primarily in increasing the likelihood of convergence rather than accelerating convergence. However, this optimal choice does not guarantee convergence, since convergence depends on the functionf(x), the constraint (x), and the initialx chosen in order to start the algorithm.This research, supported by the National Science Foundation, Grant No. GP-18522, is based on Ref. 1.     

Smooth solutions to some differential-difference equations of neutral type

The paper is devoted to the scalar linear differential-difference equation of neutral type

Optimal boundary displacement control of string vibrations with a nonlocal evenness condition of the second kind

We study the behavior of a string with the nonlocal boundary condition u _x (l, t) = u _x ($ x^\circ $ x^\circ , t). A displacement control u(0, t) = μ(t) bringing the string from an arbitrarily given initial state to an arbitrarily given terminal state is applied at the left endpoint of the string. For the initial and terminal functions, we find necessary and sufficient conditions for the controllability of the string. Under these conditions, we carry out optimization; i.e., of all admissible controls, we choose a control minimizing the boundary energy integral.     

A penalty function proof of a Lagrange multiplier theorem with application to linear delay systems

Using a penalty function method, a Lagrange multiplier theorem in dual Banach spaces is proved. This theorem is applied to the optimal control of linear, autonomous time-delay systems with function space equality end condition and pointwise control restrictions. Under an additional regularity condition, the resulting Lagrange multiplier can be identified with an element ofL .     

Local and Global Existence of Solutions to Initial Value Problems of Modified Nonlinear Kawahara Equations

This paper is devoted to studying the initial value problem of the modified nonlinear Kawahara equation the first partial dervative of u to t ,the second the third ＋α the second partial dervative of u to x ,the second the third ＋β the third partial dervative of u to x ,the second the thire ＋γ the fifth partial dervative of u to x = 0,（x,t）∈R^2.We first establish several Strichartz type estimates for the fundamental solution of the corresponding linear problem. Then we apply such estimates to prove local and global existence of solutions for the initial value problem of the modified nonlinear Karahara equation. The results show that a local solution exists if the initial function uo（x） ∈ H^s（R） with s ≥ 1/4, and a global solution exists if s ≥ 2.     

A minimax optimal control problem

A control system x=f(t,x,u) is considered, and a cost functional ess supT ₀tT ₁ G(t, x(t),u(t)) is to be minimized. Necessary conditions for optimality (maximum principle and transversality conditions) are derived. It is also shown that an optimal control is optimal for the corresponding problem on a subinterval of [T ₀,T ₁], if a certain controllability condition is satisfied.     

The radial basis functions method for identifying an unknown parameter in a parabolic equation with overspecified data

Parabolic partial differential equations with overspecified data play a crucial role in applied mathematics and engineering, as they appear in various engineering models. In this work, the radial basis functions method is used for finding an unknown parameter p(t) in the inverse linear parabolic partial differential equation u_t = u_xx + p(t)u + φ, in [0,1] × (0,T], where u is unknown while the initial condition and boundary conditions are given. Also an additional condition ∫₀¹k(x)u(x,t)dx = E(t), 0 ≤ t ≤ T, for known functions E(t), k(x), is given as the integral overspecification over the spatial domain. The main approach is using the radial basis functions method. In this technique the exact solution is found without any mesh generation on the domain of the problem. We also discuss on the case that the overspecified condition is in the form ∫₀^s(t) u(x,t)dx = E(t), 0 < t ≤ T, 0 < s(t) < 1, where s and E are known functions. Some illustrative examples are presented to show efficiency of the proposed method. © 2007 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2007     

Study of linear information for classes of polynomial equations

Summary We study linear sequential (adaptive) information for approximating zeros of polynomials of unbounded degree and establish a theorem on constrained approximation of smooth functions by polynomials.For a positive we seek a pointx ^* such that|x ^* – _p | , where _p is a zero of a real polynomialp in the interval [a, b]. We assume thatp belongs to the classF ₁ of polynomials of bounded arbitrary seminorm and having a root in [a, b] or to the classF ₂ of polynomials which are nonpositive ata, nonnegative atb and have exactly one simple zero in [a, b]. The information onp consists ofn sequential (adaptive) evaluations of arbitrary linear functionals. The pointx ^* is constructed by means of an algorithm which is an arbitrary mapping depending on the information onp. We show that there exists no information and no algorithm for computingx ^* for everyp fromF ₁, no matter how large the value ofn is. This is a stronger result than that obtained by us for smooth functions.For the classF ₂ we can find a pointx ^* for arbitraryp and. Anoptimal algorithm, i.e., an algorithm with the smallest error, is thebisection of the smallest known interval containing the root ofp. We also exhibitoptimal information operators, i.e., the linear functionals for which the error of an optimal algorithm that uses them is minimal. It turns out that in the class of nonsequential (parallel) information, i.e., when the functionals are given simultaneously, optimal information consists of the evaluations of a polynomial atn-equidistant points in [a, b]. In the class of sequential continuous information, optimal information consists of evaluations of a polynomial atn points generated by thebisection method. To prove this result we establish a theorem on constrained approximation of smooth functions by polynomials. More precisely, we prove that a smooth function can be arbitrarily well uniformly approximated by a polynomial which satisfies constrains given byn arbitrary continuous linear functionals.Our results indicate that the problem of finding an -approximation to a real zero of a real polynomial (of unknown degree) is essentially of the same difficulty as the problem of finding an -approximation to a zero of an infinitely differentiable function.     

Optimal solution of nonlinear equations satisfying a Lipschitz condition

Summary For a given nonnegative we seek a pointx ^* such that |f(x ^*)| wheref is a nonlinear transformation of the cubeB=[0,1] ^m into (or ^p ,p>1) satisfying a Lipschitz condition with the constantK and having a zero inB.The information operator onf consists ofn values of arbitrary linear functionals which are computed adaptively. The pointx ^* is constructed by means of an algorithm which is a mapping depending on the information operator. We find an optimal algorithm, i.e., algorithm with the smallest error, which usesn function evaluations computed adaptively. We also exhibit nearly optimal information operators, i.e., the linear functionals for which the error of an optimal algorithm that uses them is almost minimal. Nearly optimal information operators consists ofn nonadaptive function evaluations at equispaced pointsx _j in the cubeB. This result exhibits the superiority of the T. Aird and J. Rice procedure ZSRCH (IMSL library [1]) over Sobol's approach [7] for solving nonlinear equations in our class of functions. We also prove that the simple search algorithm which yields a pointx ^*=x _k such that is nearly optimal. The complexity, i.e., the minimal cost of solving our problem is roughly equal to (K/) ^m .     

A greedy algorithm for the optimal basis problem

The following problem is considered. Givenm+1 points {x _i }₀ ^m inR ⁿ which generate anm-dimensional linear manifold, construct for this manifold a maximally linearly independent basis that consists of vectors of the formx _i −x _j . This problem is present in, e.g., stable variants of the secant and interpolation methods, where it is required to approximate the Jacobian matrixf′ of a nonlinear mappingf by using values off computed atm+1 points. In this case, it is also desirable to have a combination of finite differences with maximal linear independence. As a natural measure of linear independence, we consider the hadamard condition number which is minimized to find an optimal combination ofm pairs {x _i ,x _j }. We show that the problem is not NP-hard, but can be reduced to the minimum spanning tree problem, which is solved by the greedy algorithm inO(m ²) time. The complexity of this reduction is equivalent to onem×n matrix-matrix multiplication, and according to the Coppersmith-Winograd estimate, is belowO(n ^2.376) form=n. Applications of the algorithm to interpolation methods are discussed. Part of the work was done while the author was visiting DIMACS, an NSF Science and Technology Center funded under contract STC-91-19999; DIMACS is a cooperative project of Rutgers University, Princeton University, AT&T Bell Laboratories and Bellcore, NJ, USA.     

A 2D kernel determination problem in a visco-elastic porous medium with a weakly horizontally inhomogeneity

We consider a system of hyperbolic integro-differential equations of SH waves in a visco-elastic porous medium. In this work, it is assumed that the visco-elastic porous medium has weakly horizontally inhomogeneity. The direct problem is the initial-boundary problem: the initial data is equal to zero, and the Neumann-type boundary condition is specified at the half-plane boundary and is an impulse function. As additional information, the oscillation mode of the half-plane line is given. It is assumed that the unknown kernel has the form K(x,t)=K₀(t)+ϵxK₁(t)+…, where ϵ is a small parameter. In this work, we construct a method for finding K₀,K₁ up to a correction of the order of O(ϵ²).     

A Globally Convergent Algorithm for a PDE-Constrained Optimization Problem Arising in Electrical Impedance Tomography

We study the convergence properties of an algorithm for the inverse problem of electrical impedance tomography, which can be reduced to a partial differential equation (PDE) constrained optimization problem. The direct problem consists of the potential equation div(??u) = 0 in a circle, with Neumann condition describing the behavior of the electrostatic potential in a medium with conductivity given by the function ?(x, y). We suppose that at each time a current ψ _i is applied to the boundary of the circle (Neumann's data), and that it is possible to measure the corresponding potential ? _i (Dirichlet data). The inverse problem is to find ?(x, y) given a finite number of Cauchy pairs measurements (? _i , ψ _i ), i = 1,…, N. The problem is formulated as a least squares problem, and the developed algorithm solves the continuous problem using descent iterations in its corresponding finite element approximations. Wolfe's conditions are used to ensure the global convergence of the optimization algorithm for the continuous problem. Although exact data are assumed, measurement errors in data and regularization methods shall be considered in a future work.