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Title: Centralized Stochastic Optimal Control of Complex Systems

In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.
  1. ORNL
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Conference: 2015 European Control Conference, Linz, IL, Austria, 20150715, 20150717
Research Org:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). National Transportation Research Center (NTRC)
Sponsoring Org:
ORNL LDRD Seed-Money
Country of Publication:
United States
complex systems; stochastic optimal control; Markov chain