Stochastic Linear Regulator Problem in Optimal Control Theory

Stochastic optimization problems are the study of dynamical systems subject to random perturbations which can be controlled in order to optimize some performance criterion. The research on control theory has developed considerably over last few years, inspired in particular by stochastic optimization problems emerging from mathematical nance. Problems involving linear dynamics and quadratic performance criteria are generally called linear regulator problems. The usual framework of control is the one given in probably the most studied control problem, the linear quadratic optimal control problem or the linear regulator problem, which deals with minimizing a performance index of a system governed by a set of dierential equations. The object of linear regulator control problems is to control the position of a certain process and at the same time, the force with which this process is being regulated, by punishing quadratic deviations from some targets of the process and the rate of regulation, respectively.

Autorentext

Teaching in Statistics, Shahjalal University of Science and Technology (SUST), since 1995 and promoted as a full Professor in 2011. PhD in Statistics and Postdoctoral in Operations Research, several research projects, thesis reviewed. Published more than 55 articles and now working in Universiti Utara Malaysia as a Visiting Associate Professor.