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AUTOMATICA
2007
111views more  AUTOMATICA 2007»
13 years 5 months ago
A stable block model predictive control with variable implementation horizon
— In this paper, we present a stable receding horizon model predictive control for discrete-time nonlinear systems. The standard MPC scheme is modified to incorporate (1) a bloc...
Jing Sun, Ilya V. Kolmanovsky, Reza Ghaemi, Shuhao...
IWANN
2005
Springer
13 years 10 months ago
Input Selection for Long-Term Prediction of Time Series
Prediction of time series is an important problem in many areas of science and engineering. Extending the horizon of predictions further to the future is the challenging and diffic...
Jarkko Tikka, Jaakko Hollmén, Amaury Lendas...
CDC
2010
IEEE
122views Control Systems» more  CDC 2010»
12 years 12 months ago
On optimal input design in system identification for control
Abstract-- This paper considers a recently proposed framework for experiment design in system identification for control. We will consider model based control design methods, such ...
Bo Wahlberg, Håkan Hjalmarsson, Mariette Ann...
ENGL
2007
81views more  ENGL 2007»
13 years 4 months ago
Computational Comparisons of GPC and NGPC Schemes
—In this paper the GPC and NGPC model predictive control techniques are applied to a typical plant and compared in terms of computational efficiency. The system identification an...
D. N. Rao, M. R. K. Murthy, D. N. Harshal, S. R. M...
AROBOTS
2011
12 years 12 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox