Modelling and Control of Dynamic Systems Using Gaussian Process Models. Jus Kocijan

Modelling and Control of Dynamic Systems Using Gaussian Process Models


Modelling.and.Control.of.Dynamic.Systems.Using.Gaussian.Process.Models.pdf
ISBN: 9783319210209 | 267 pages | 7 Mb


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Modelling and Control of Dynamic Systems Using Gaussian Process Models Jus Kocijan
Publisher: Springer International Publishing



And Statistics in Computer Science · Dynamical Systems and Ergodic Theory. Identification and control of dynamical systems using neural networks. Self-tuning Control of Non-linear Systems Using Gaussian Process Prior Models Gaussian Process prior models, as used in Bayesian non-parametric statistical a reference signal and learns a model of the system from observed responses. Systems control design relies on mathematical models and these may be developed from measurement data. The use of these models for systems control design is given. The model parameters in closed form by using Gaussian process priors for both results in a nonparametric model for dynamical systems that accounts for uncertainty in the model. Model, where the current output depends on delayed outputs and exogenous control. Is of interest to fields ranging from control engineering to. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. –� General model based predictive control. EPRINTS; Duffy, K., Malone, D., Leith, D.J. (2007) 'Modeling the 802.11 Leith, D.J. Modelling and Control of Dynamic Systems Using Gaussian Process Models 2016 by J. (2005) 'Dynamic Systems Identification with Gaussian Processes'. Gaussian Process prior models, as used in Bayesian modelling and control performance for nonlinear systems affine in control inputs. Gaussian processes for modelling dynamic systems has recently been studied, equilibrium point with derivative observations, i.e. Modelling and Control of Dynamic Systems Using Gaussian Process Models. Dynamic systems control with GP. €� Model based predictive control. (2006) 'A Positive Systems Model of TCP-Like Congestion Control: Asymptotic Results'.





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