When dealing with industrial systems it is pertinent to consider extending the linear self-tuning framework to include a knowledge of inherent plant nonlinearities. In heat transfer processes, the nonlinearities that arise may be represented by bilinear characteristics. Indeed, when systems exhibit bilinear characteristics it is not unreasonable to consider accommodating the bilinearity into the model structure within an extended self-tuning control framework and, in this respect, novel bilinear self-tuning control strategies are proposed. This paper describes the development of novel bilinear self-tuning pole-placement and generalised predictive control strategies and reports on their effectiveness when applied to an industrial heat treatment furnace. To provide for a realistic comparison, the performances achieved using the bilinear schemes are compared to that achieved when use is made of an existing autotuned industrial PID controller; their respective performances are quantified in terms of a devised measure of effectiveness. The results are very encouraging and indicate that, by adopting the bilinear self-tuning approach, significant potential improvements over existing state of the art controllers are possible.