KERNEL METHODS FOR DYNAMICAL SYSTEM IDENTIFICATION

Kernel methods are a family of methods that have recently found a constantly increasing interest in the machine learning community. Commonly used methods, such as Gaussian process regression or Tikhonov regularization are in this category. These methods are used to estimate an unknown function from a dataset, and have found diffusion especially in the machine learning community...
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FAULT DIAGNOSIS AND CONDITION MONITORING

Fault diagnosis is an established field of control systems. However, due to the intrinsic characteristics of the processes being monitored, fault detection and health monitoring methodologies need to be adapted for the particular problem at hand. The aim of this research area is to develop fault detection and condition assessment algorithms for industrial applications, drawing ...
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