Markov chain modeling approaches for on board applications

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.