A new approach to nonlinear Projection to Latent Structures (PLS) modelling using Radial Basis Function (RBF) neural networks to provide a nonlinear inner relationship is described, along with a hybrid optimisation technique for training the networks. Results are given showing an improvement in modelling performance over linear PLS for a variety of problems. An application of the technique to fault detection on a validated model of an industrial distillation plant is also demonstrated.
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