Markov jump linear systems constitute a class of hybrid systems, the dynamics of which are described by the switching among linear forms, while the switching process is modelled as a Markov chain. These systems are sufficiently specialized to allow for computational algorithms and for strong results extending ideas and concepts of deterministic linear systems. They have deserved much attention and there is nowadays a wide range of applications, for example in economy and aeronautics. In this talk we present a background on Markov jump linear systems and an overview of the research, including the LQ problem and available methods of solutions, some structural notions such as stochastic concepts of detectability and stabilizability, and the role that they play in optimal control and filtering (here we include some current research).
Back to Control Seminars Page.