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ESANN
2001
15 years 7 months ago
A divide-and-conquer learning architecture for predicting unknown motion
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
Patrice Wira, Jean-Philippe Urban, Julien Gresser
AUTOMATICA
2007
68views more  AUTOMATICA 2007»
15 years 6 months ago
A risk adjusted approach to robust simultaneous fault detection and isolation
: In this paper we address the problem of detecting and isolating faults from noisy input/output measurements of a MIMO uncertain–system, subject to structured dynamic uncertaint...
Wenjing Ma, Mario Sznaier, Constantino M. Lagoa
AAAI
1998
15 years 7 months ago
Structured Representation of Complex Stochastic Systems
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
Nir Friedman, Daphne Koller, Avi Pfeffer
NN
2008
Springer
158views Neural Networks» more  NN 2008»
15 years 6 months ago
Optimal wide-area monitoring and nonlinear adaptive coordinating neurocontrol of a power system with wind power integration and
Wide-area coordinating control is becoming an important issue and a challenging problem in the power industry. This paper proposes a novel optimal wide-area coordinating neurocont...
Wei Qiao, Ganesh K. Venayagamoorthy, Ronald G. Har...
CDC
2010
IEEE
150views Control Systems» more  CDC 2010»
15 years 1 months ago
Nonlinear hybrid system identification with kernel models
Abstract-- This paper focuses on the identification of nonlinear hybrid systems involving unknown nonlinear dynamics. The proposed method extends the framework of [1] by introducin...
Fabien Lauer, Gérard Bloch, René Vid...