Now showing items 1-4 of 4
Identification of nonlinearities in dynamic process systems
Process modelling is an essential element in the development of advanced (model-based) process control systems, accounting for up to 80% of the cost of development. Often, models based on historic process data are the only ...
Classification of process dynamics with Monte Carlo singular spectrum analysis
Identification of non-linear systems can be a daunting task and in the process industries the problem is complicated considerably by the presence of noise from various sources, non-stationarity of the data and intermittence, ...
Non-linear system identification of an autocatalytic reactor using least squares support vector machines
The concepts behind support vector machines are very interesting both in theory and in practice, as they are based on a universal constructive learning procedure derived from the statistical learning theory developed by ...
Monitoring of an industrial liquid-liquid extraction system with kernel-based methods
The behaviour of liquid-liquid extraction systems can be complex and as a result linear methods of process condition monitoring such as principal component analysis or partial least squares may not be able to detect and ...