This brief broadens readers' understanding of stochastic control by highlighting recent advances in the design of optimal control for Markov jump linear systems (MJLS). It also presents an algorithm that attempts to solve this open stochastic control problem, and provides a real-time application for controlling the speed of direct current motors, illustrating the practical usefulness of MJLS. Particularly, it offers novel insights into the control of systems when the controller does not have access to the Markovian mode.

Broadens readers' understanding of Markov jump linear systems Details recent advances in the control of stochastic systems Illustrates the usefulness of Markov jump linear systems using a real-time application Includes supplementary material: sn.pub/extras

Klappentext

This brief broadens readers understanding of stochastic control by highlighting recent advances in the design of optimal control for Markov jump linear systems (MJLS). It also presents an algorithm that attempts to solve this open stochastic control problem, and provides a real-time application for controlling the speed of direct current motors, illustrating the practical usefulness of MJLS. Particularly, it offers novel insights into the control of systems when the controller does not have access to the Markovian mode.

Inhalt
Preliminaries.- Finite-Time Control Problem.- Approximation of the Optimal Long-Run Average-Cost Control Problem.- References.