Advances In The Control Of Markov Jump Linear Systems With No Mode Observation (springerbriefs In Electrical And Computer Engineering)
by Alessandro N. Vargas /
2016 / English / PDF, DjVu
1.5 MB Download
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 modeAuthors: Vargas, Alessandro N., Costa, Eduardo F., do Val, Joo B. R.
Broadens readers understanding of Markov jump linear systemsDetails recent advances in the control of stochastic systemsIllustrates the usefulness of Markov jump linear systems using a real-time application
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.
Number of Illustrations and Tables
2 b/w illustrations, 6 illustrations in colour
Topics
Control
Systems Theory, Control
Probability Theory and Stochastic Processes
Operator Theory
