Gaussian Process Repetitive Control for Suppressing Spatial Disturbances

Gaussian Process for Internal Model Control

Abstract — To improve transparency and reduce the curse of dimensionality of non–linear black–box models, the local modelling approach was proposed. Poor transient response of Local Model networks led to the use of non–parametrical probabilistic models such as the Gaussian Process prior approach. Recently, Gaussian Process models were applied in the Minimum Variance Control. This paper introduc...

Gaussian Process Optimization for Self-Tuning Control

Gaussian Process Models of Spatial Aggregation Algorithms

Multi-level spatial aggregates are important for data mining in a variety of scientific and engineering applications, from analysis of weather data (aggregating temperature and pressure data into ridges and fronts) to performance analysis of wireless systems (aggregating simulation results into configuration space regions exhibiting particular performance characteristics). In many of these appl...

Gaussian Process Models in Spatial Data Mining

ion of GeoDatabases Geographic Database Conceptual Modeling Modeling with a UML Profile Geographic Databases Spatio-temporal Database Modeling with an Extended Entity-Relationship Model Geographic Dynamics, Visualization and Modeling MAY YUAN Department of Geography and Center for Spatial Analysis, University of Oklahoma, Norman, OK, USA

Filtered-X LMS vs repetitive control for active structural acoustic control of periodic disturbances

This paper presents a comparison of repetitive control and narrowband filtered-X LMS feedforward control, both applicable in the field of active structural acoustic control (ASAC) and active noise control (ANC) of periodic disturbances. This can be useful for example in rotating machinery, where the disturbance is often determined by the rotational speed. A frequency domain relation between the...