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» Nonlinear Predictive Control with a Gaussian Process Model
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NIPS
1993
15 years 3 months ago
Mixtures of Controllers for Jump Linear and Non-Linear Plants
We describe an extension to the Mixture of Experts architecture for modelling and controlling dynamical systems which exhibit multiple modesof behavior. This extension is based on...
Timothy W. Cacciatore, Steven J. Nowlan
ICDM
2005
IEEE
165views Data Mining» more  ICDM 2005»
15 years 7 months ago
A Bernoulli Relational Model for Nonlinear Embedding
The notion of relations is extremely important in mathematics. In this paper, we use relations to describe the embedding problem and propose a novel stochastic relational model fo...
Gang Wang, Hui Zhang, Zhihua Zhang, Frederick H. L...
CDC
2008
IEEE
139views Control Systems» more  CDC 2008»
15 years 8 months ago
Iterative Risk Allocation: A new approach to robust Model Predictive Control with a joint chance constraint
Abstract— This paper proposes a novel two-stage optimization method for robust Model Predictive Control (RMPC) with Gaussian disturbance and state estimation error. Since the dis...
Masahiro Ono, Brian C. Williams
119
Voted
ICAS
2006
IEEE
139views Robotics» more  ICAS 2006»
15 years 8 months ago
Predicting Resource Demand in Dynamic Utility Computing Environments
— We target the problem of predicting resource usage in situations where the modeling data is scarce, non-stationary, or expensive to obtain. This scenario occurs frequently in c...
Artur Andrzejak, Sven Graupner, Stefan Plantikow
IROS
2008
IEEE
123views Robotics» more  IROS 2008»
15 years 8 months ago
Learning predictive terrain models for legged robot locomotion
— Legged robots require accurate models of their environment in order to plan and execute paths. We present a probabilistic technique based on Gaussian processes that allows terr...
Christian Plagemann, Sebastian Mischke, Sam Prenti...