Radial Basis Function Networks Applied to Process Control

There are strong relationships between radial basis function (RBF) approaches and neural network representations. Indeed, the RBF representation can be implementated in the form of a two-layered network. This paper examines the contribution that RBF networks can make to the process modelling and control toolbox. Radial basis function networks are compared with sigmoidal activation function feedforward networks using data from a large industrial process.