Title :
Markov chain modeling approaches for on board applications
Author :
Filev, D.P. ; Kolmanovsky, I.
Author_Institution :
Ford Motor Co., Dearborn, MI, USA
fDate :
June 30 2010-July 2 2010
Abstract :
This paper is concerned with Markov chain modeling of operating conditions and system dynamics to facilitate application of stochastic dynamic programming and stochastic model predictive control techniques. We discuss and compare two modeling frameworks based on interval and fuzzy encoding of the signal being modeled. We also present a recursive algorithm for on-line identification of such models. Examples based on automotive vehicle speed and road grade modeling are presented.
Keywords :
Markov processes; dynamic programming; encoding; fuzzy control; fuzzy set theory; predictive control; recursive estimation; stochastic programming; Markov chain model; automotive vehicle speed; fuzzy encoding; predictive control; recursive algorithm; road grade modeling; stochastic dynamic programming; system dynamics; Dynamic programming; Encoding; Frequency estimation; Fuzzy set theory; Predictive control; Predictive models; State-space methods; Stochastic systems; USA Councils; Vehicle dynamics;
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-7426-4
DOI :
10.1109/ACC.2010.5530610
