Olga Kostyukova

Robust optimal feedback for terminal linear-quadratic control problems under disturbances

We consider a linear dynamic system in the presence of an unknown but bounded perturbation and study how to control the system in order to get into a prescribed neighborhood of a zero at a given final moment. The quality of a control is estimated by the quadratic functional. We define optimal guaranteed program controls as controls that are allowed to be corrected at one intermediate time moment. We show that an infinite dimensional problem of constructing such controls is equivalent to a special bilevel problem of mathematical programming which can be solved explicitely. An easy implementable algorithm for solving the bilevel optimization problem is derived. Based on this algorithm we propose an algorithm of constructing a guaranteed feedback control with one correction moment. We describe the rules of computing feedback which can be implemented in real time mode. The results of illustrative tests are given.

Covariance Matrices for Parameter Estimates of Constrained Parameter Estimation Problems

In this paper we show how, based on the conjugate gradient method, to compute the covariance matrix of parameter estimates and confidence intervals for constrained parameter estimation problems as well as their derivatives.

Analysis of Properties of the Solutions to Parametric Time-Optimal Problems

We consider a linear time-optimal problem in which initial state values depend on a parameter and study the problem of the solution structure identification for small parameter perturbations. Properties of the time-optimal function and a point-set mapping, defined by optimal Lagrange vectors, are studied as well as the dependence of the solution on the parameter. Special attention is paid to the solution properties in irregular points.

Parametric optimal control problems with weighted L 1-norm in the cost function

In the paper, an optimal control problem with weighted L1-norm in the cost function is studied. The problem is considered as a parametric problem where L1-norm weight ratio is treated as a parameter. We analyze the dependence of solution to the mentioned optimization problem on values of the parameter. A theorem that describes properties of the solution under small parameter perturbations is proved. Differential properties of the solution are investigated. Under assumption that a solution to unperturbed problem is known, rules for construction of solutions to perturbed optimization problems are given.

Optimality Conditions for Convex Semi-infinite Programming Problems with Finitely Representable Compact Index Sets

In the present paper, we analyze a class of convex semi-infinite programming problems with arbitrary index sets defined by a finite number of nonlinear inequalities. The analysis is carried out by employing the constructive approach, which, in turn, relies on the notions of immobile indices and their immobility orders. Our previous work showcasing this approach includes a number of papers dealing with simpler cases of semi-infinite problems than the ones under consideration here. Key findings of the paper include the formulation and the proof of implicit and explicit optimality conditions under assumptions, which are less restrictive than the constraint qualifications traditionally used. In this perspective, the optimality conditions in question are also compared to those provided in the relevant literature. Finally, the way to formulate the obtained optimality conditions is demonstrated by applying the results of the paper to some special cases of the convex semi-infinite problems.

Reconstruction of the Surface Heat Flux for a Quasi-linear System of the Hyperbolic Type Heat-Conduction Equations

The problem of the identification of the surface heat flux for a quasi-linear system of the hyperbolic type heat-conduction equations is studied. An approach is proposed based on the stage-by-stage suboptimal optimization of the cost functional and input data filtering using the HuberTikhonov functional. Results are presented for the numerical modeling of the identification problem in conditions of both standard noisy data and noise emissions.

Computing Covariance Matrices for Constrained Nonlinear Large Scale Parameter Estimation Problems Using Krylov Subspace Methods

In the paper we show how, based on the preconditioned Krylov subspace methods, to compute the covariance matrix of parameter estimates, which is crucial for efficient methods of optimum experimental design.

New Necessary Conditions for Optimal Control Problems in Discontinuous Dynamic Systems

In the paper we derive new necessary optimality conditions for optimal control of differential equations systems with discontinuous right hand side. The main attention is paid to a situation when an optimal trajectory slides on the discontinuity surface. The new conditions, derived in the paper, are essential and do not follow from any known necessary conditions for such systems.