The adaptive linear quadratic Gaussian control problem, where the linear transformation of the state A and the linear transformation of the control B are unknown, is solved assuming only that (A; B) is controllable and (A; Q 1 ) is observable, where Q 1 determines the quadratic form for the state in the integrand of the cost functional. A weighted least squares algorithm is modified by using a ...

‎In this paper‎, ‎Haar wavelets are performed for solving continuous time-variant linear-quadratic optimal control problems‎. ‎Firstly‎, ‎using necessary conditions for optimality‎, ‎the problem is changed into a two-boundary value problem (TBVP)‎. ‎Next‎, ‎Haar wavelets are applied for converting the TBVP‎, ‎as a system of differential equations‎, ‎in to a system of matrix algebraic equations‎...

<p style='text-indent:20px;'>In this paper, an optimal control model ruled by a class of linear discrete-time stochastic descriptor systems is considered under quadratic index performance. Employing dynamic programming method, recurrence equation to simplify the problem presented provided that are both regular and impulse-free. When objective function quadratic, according equation, linear...

Inspired by the successes of stochastic algorithms in training deep neural networks and simulation interacting particle systems, we propose analyze a framework for randomized time-splitting linear-quadratic optimal control. In our proposed framework, linear dynamics original problem is replaced dynamics. To obtain dynamics, system matrix split into simpler submatrices time interval interest sub...