INTERNAL MODEL-PREDICTIVE CONTROL (IMPC)

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.