Additive internal model control: an application with neural models in a kiln

In this article a new control strategy is proposed: additive internal model control. This control strategy is based in two existing strategies: additive feedforward control and internal model control. Internal model control is composed of an inverse model connected in series with the plant and a forward model connected in parallel with the plant, this structure allows the error feedback to reflect the effect of disturbance and plant mismodelling resulting in a robust control loop. Additive feedforward control consists of introducing an extra controller into an existing loop with the purpose of improving the quality of the control action. This new controller introduced is a feedforward controller, which performs better than the existing controller. In the proposed strategy, additive internal model control, the new controller added to the control loop is an internal model controller. The new control strategy is tested in a temperature control loop of a reduced scale prototype kiln resulting in improved performance compared to additive feedforward control. The models used to implement the control strategies are built with feedforward neural networks.