https://murray.cds.caltech.edu/index.php?title=On_the_Control_of_Jump_Linear_Markov_Systems_with_Markov_State_Estimation&feed=atom&action=historyOn the Control of Jump Linear Markov Systems with Markov State Estimation - Revision history2022-08-08T14:33:54ZRevision history for this page on the wikiMediaWiki 1.37.2https://murray.cds.caltech.edu/index.php?title=On_the_Control_of_Jump_Linear_Markov_Systems_with_Markov_State_Estimation&diff=19943&oldid=prevMurray: htdb2wiki: creating page for 2002i_gmh03-acc.html2016-05-15T06:18:59Z<p>htdb2wiki: creating page for 2002i_gmh03-acc.html</p>
<p><b>New page</b></p><div>{{HTDB paper<br />
| authors = Vijay Gupta, Richard M. Murray, Babak Hassibi<br />
| title = On the Control of Jump Linear Markov Systems with Markov State Estimation<br />
| source = 2003 American Control Conference<br />
| year = 2002<br />
| type = Conference <br />
Paper<br />
| funding = AFOSR/info<br />
| url = http://www.cds.caltech.edu/~murray/preprints/gmh03-acc.pdf<br />
| abstract = <br />
We analyze a jump linear Markov system being stabilized using a zero-order hold controller. We consider the case when the Markov state is associated with the probability distribution of a measured variable. We assume that the Markov state is not known, but rather is being estimated based on the observations of the variable. We present conditions for the stability of such a system and also solve the optimal LQR control problem for the case when the state estimate update uses only the last observation value. In particular we consider a suboptimal causal version of the Viterbi estimation algorithm and show that a separtion property does not hold between the optimal control and the Markov state estimate. Some simple examples are also presented.<br />
<br />
| flags = <br />
| tag = gmh03-acc<br />
| id = 2002i<br />
}}</div>Murray