Predictive functional control (PFC), a model pre- dictive control algorithm, has been proven to be very suc- cessful in a wealth of industrial applications due to its many laudable attribute, such as its s implicity and intuitive appeal. For simple single input single output processes, PFC applica- tions use a first-order plus delay internal model and, as long as such models improve the control over classical control strategies, then their use remains justified. In this paper, a higher order internal PFC model is considered in order to reduce any possible plant-model mismatch, where the inter- nal model is formulated as a series of cascaded or parallel first-order systems. The control approach is compared to a more conventional over parameterized dynamical matrix control (DMC) approach, used extensively for Multi-Input Multi-Output systems in the petrochemical industry. This paper demonstrates the benefits of the PFC higher order formulation for a typical milk pasteurisation plant, with sig- nificant improvements in the variances of both controlled and manipulated variables when compared to a first-order PFC. In this aspect, the higher order controller competes well with DMC performances, however, using a much more sim- pler and compact internal model form.