A multiple model, state feedback strategy for robust control of non-linear processes

The major limitation of reported multiple model approaches is that robustness against process/controller disturbances cannot be addressed for processes consisting of hybrid stable/unstable regimes, or with chaotic dynamics. In this paper, a significantly modified multiple model approach is developed to achieve robust control with global stability. The new advances include: (1) stabilization of open-loop unstable plants using a state feedback strategy, (2) incorporation of an adjustable pre-filter to achieve offset-free control, (3) implementation of a Kalman filter for state estimation, and (4) connection of the multiple model approach with non-linear model predictive control to achieve a precise control objective. The improved controller design method is successfully applied to two non-linear processes with different chaotic behaviour. Compared with conventional methods without model modifications, the new approach has achieved significant improvement in control performance and robustness with a dramatically reduced number of local models.