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CDC
2009
IEEE
172views Control Systems» more  CDC 2009»
15 years 2 months ago
Approximate dynamic programming using fluid and diffusion approximations with applications to power management
—TD learning and its refinements are powerful tools for approximating the solution to dynamic programming problems. However, the techniques provide the approximate solution only...
Wei Chen, Dayu Huang, Ankur A. Kulkarni, Jayakrish...
AUTOMATICA
2008
152views more  AUTOMATICA 2008»
14 years 9 months ago
A design methodology for switched discrete time linear systems with applications to automotive roll dynamics control
In this paper we consider the asymptotic stability of a class of discrete-time switching linear systems, where each of the constituent subsystems is Schur stable. We first present...
Selim Solmaz, Robert Shorten, Kai Wulff, Fiacre &O...
ICANN
2010
Springer
14 years 10 months ago
Reinforcement Learning Based Neural Controllers for Dynamic Processes without Exploration
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
Frank-Florian Steege, André Hartmann, Erik ...
IOR
2008
105views more  IOR 2008»
14 years 9 months ago
The Stochastic Knapsack Revisited: Switch-Over Policies and Dynamic Pricing
The stochastic knapsack has been used as a model in wide ranging applications from dynamic resource allocation to admission control in telecommunication. In recent years, a variat...
Grace Y. Lin, Yingdong Lu, David D. Yao
CDC
2009
IEEE
122views Control Systems» more  CDC 2009»
14 years 7 months ago
Reduced complexity models in the identification of dynamical networks: Links with sparsification problems
In many applicative scenarios it is important to derive information about the topology and the internal connections of more dynamical systems interacting together. Examples can be ...
Donatello Materassi, Giacomo Innocenti, Laura Giar...