Necessary optimality conditions for a linear incomplete feedback controller for stochastic systems operating on an unbounded time interval are proved. Numerical methods for optimal controller synthesis that ensure the system’s stability and cost optimality of stabilization with respect to a given criterion are proposed. The stabilization problem for an orbit of an Earth satellite under disturbances and different compositions of measurements is considered.

The present paper focuses on identification issues of the micro- and macrocharacteristics of social networks proposed in [1]. For this, we employ data on real online social networks—Facebook, LiveJournal and Twitter. And finally, the results of corresponding simulation experiments are provided and compared.

This paper considers the feasibility of using the optimal parameters of stationary inventory control policies to design inventory control rules in supply systems operating on a real market. The efficiency of the long-sighted and myopic inventory control policies is compared. Different approaches to design the optimal stationary policies are investigated. A comparative evaluation of these approaches is given and the specifics of their application are discussed. The optimal parameters of the stationary inventory control policies as functions of the market state and, in particular, of the inflation rate are estimated via simulation experiments

The synthesis control problem for the plane motion of a wheeled robot with constrained control resource is studied. The goal of the control is to bring the robot to an assigned curvilinear trajectory and to stabilize its motion along it. For a synthesized control law, the problem of finding the best in the sense of volume ellipsoidal approximation of the attraction domain of the target path is posed. To take into account constraints on the control, an approach based on methods of absolute stability theory is used, in the framework of which construction of an approximating ellipsoid reduces to solving a system of linear matrix inequalities. It is shown that the desired maximum-volume approximating ellipsoid can be found by solving a standard constrained optimization problem for a function of two variables.

Stabilization of motion of a wheeled robot with constrained control resource by means of a continuous feedback linearizing the closed-loop system in a neighborhood of the target path is considered. We pose the problem of finding the feedback coefficients such that the phase portrait of the nonlinear closed-loop system is topologically equivalent to that of a linear system with a stable node, with the asymptotic rate of decrease of the deviation from the target path being as high as possible. On this family, we pose the problem of minimization of ``overshooting'' for arbitrary initial conditions. The solution of this optimization problem is proved to be a limit discontinuous control law. A hybrid control law is proposed that, on the one hand, ensures the desired properties of the phase portrait and minimal overshooting and, on the other hand, does not result in a chattering inherent in systems with discontinuous feedbacks.