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» Iterative Learning Control - Monotonicity and Optimization
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COLT
2010
Springer
13 years 4 months ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer
CDC
2009
IEEE
138views Control Systems» more  CDC 2009»
13 years 4 months ago
Beyond local optimality: An improved approach to hybrid model learning
Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...
Stephanie Gil, Brian Williams
TSMC
2002
143views more  TSMC 2002»
13 years 5 months ago
Robot visual servoing with iterative learning control
Abstract--This paper presents an iterative learning scheme for visionguided robot trajectory tracking. At first, a stability criterion for designing iterative learning controller i...
Ping Jiang, Rolf Unbehauen
EUSFLAT
2001
104views Fuzzy Logic» more  EUSFLAT 2001»
13 years 7 months ago
Iterative learning fuzzy control
In this paper an iterative learning control design method is depicted, leading to a feedforward controller minimizing tracking error of repetitive trajectories. The approach is ex...
Manuel Olivares, Pedro Albertos, Antonio Sala
CDC
2009
IEEE
106views Control Systems» more  CDC 2009»
13 years 11 months ago
Gradient methods for iterative distributed control synthesis
— In this paper we present a gradient method to iteratively update local controllers of a distributed linear system driven by stochastic disturbances. The control objective is to...
Karl Martensson, Anders Rantzer