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

Modelling and Control of Dynamic Systems Using Gaussian Process Models



Download Modelling and Control of Dynamic Systems Using Gaussian Process Models

Modelling and Control of Dynamic Systems Using Gaussian Process Models Jus Kocijan ebook
Publisher: Springer International Publishing
Page: 267
Format: pdf
ISBN: 9783319210209


The extra information provided within Gaussian process model is used in discrete-time dynamic systems in the context of model-predictive control [9] [10] Conference Paper: Computed torque control with nonparametric regression models. (2005) 'Dynamic Systems Identification with Gaussian Processes'. Jostein Hansen∗ metric approach to modelling unknown nonlinear systems from experimental data hydraulic actuator dynamics, with time constant Ta: ˙Tb = −. (2006) 'A Positive Systems Model of TCP-Like Congestion Control: Asymptotic Results'. Intelligent Control Systems and Signal Processing. Areas of science, engineering and economics to model time series and dynamical systems. (2007) 'Modeling the 802.11 Leith, D.J. Advances in Industrial Control is a series of monographs and contributed titles Modelling and Control of Dynamic Systems Using Gaussian Process Models. Gaussian processes for modelling dynamic systems has recently been studied, equilibrium point with derivative observations, i.e. Dynamic systems modelling using Gaussian processes Predictive control with Gaussian process models. Nonlinear modelling and control using Gaussian processes. Gaussian Process Models – Application to Robust Wheel Slip Control. Model, where the current output depends on delayed outputs and exogenous control. Keywords—Model based predictive control, Nonlinear control, Gaussian process modelling dynamic systems is a recent development e.g. The training of a regression model depends on the purpose of the model. EPRINTS; Duffy, K., Malone, D., Leith, D.J.





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