A computationally simple model predictive control algorithm incorporat
es the attractive features of the internal model control (IMC) law. Th
e algorithm first computes the IMC control effort via a model state fe
edback implementation that automatically compensates for past control
effort saturation. Before applying the calculated control, the algorit
hm checks to see if this control effort, when applied over a single sa
mpling interval and followed by a control effort at the opposite limit
(relative to its steady-state level), will cause the model output to
exceed its desired trajectory. If not, the calculated control is appli
ed. Otherwise the control is reduced appropriately. Application of the
new algorithm to a variety of linear single-input single-output syste
ms shows a smooth, rapid response, without significant overshoot. Comp
arisons with a QDMC algorithm, tuned to give the same unconstrained be
havior as the IMC system and the best possible constrained performance
, favor the IMPC system. Application of the new algorithm to a simple
multivariable problem drawn from web control in film manufacturing dem
onstrates the flexibility of the algorithm in dealing with control eff
ort saturation in multivariable systems.