If current research efforts worldwide on neural networks are to gain recognition and continue at their current levels, it is essential that theoretical advances are accompanied by industrial applications where the advantages/disadvantages of this new technology can be properly assessed against more conventional techniques. The past few years have seen a marked shift towards practical, as opposed to purely simulation, studies in the field of control and systems engineering, which is a healthy sign both of a maturing technology and successful technology transfer. A good selection of such applications are included in this book and the present chapter contains the results of two studies, one concerned with nonlinear modelling of a 200 MW boiler in an electrical power station [1] the other with inferential estimation of viscosity, a key quality indication in a chemical polymerisation reactor [2, 3].

Inspec keywords: boilers; viscosity; polymerisation; chemical reactors; neural nets

Other keywords: systems engineering; chemical polymerisation reactor; electrical power station; industrial applications; chemical process applications; neural networks; nonlinear modelling; control engineering; viscosity; technology transfer; power 200 MW

Subjects: Steam power stations and plants