Bootstrap control

In this paper, we present a new way to control linear stochastic systems. The method is based on statistical bootstrap techniques. The optimal future control signal is derived in such a way that unknown noise distribution and uncertainties in parameter estimates are taken into account. This is achie...

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Veröffentlicht in:	IEEE transactions on automatic control 2006-01, Vol.51 (1), p.28-37
Hauptverfasser:	Aronsson, M., Arvastson, L., Holst, J., Lindoff, B., Svensson, A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Computer science control theory systems control Control systems Control theory. Systems Estimates Exact sciences and technology Feedback loop Generalized predictive control Matematik Mathematical analysis Mathematics Modelling and identification Natural Sciences Naturvetenskap Noise Open loop systems Optimal control Optimization Parameter estimation Probability Theory and Statistics Process control quality control resampling Sannolikhetsteori och statistik statistical bootstrap techniques Statistical distributions statistical process statistical process control stochastic control Stochastic processes Stochastic systems Time varying systems Uncertainty
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