This article concerns non-linear control of single-input-single-output
processes with input constraints and deadtimes. The problem of input-
output linearization in continuous time is formulated as a model-predi
ctive control problem, for processes with full-state measurements and
for processes with incomplete state measurements and deadtimes. This m
odel-predictive control formulation allows one (i) to establish the co
nnections between model-predictive and input-output linearizing contro
l methods; and (ii) to solve directly the problems of constraint handl
ing and windup in input-output linearizing control. The derived model-
predictive control laws have the shortest possible prediction horizon
and explicit analytical form, and thus their implementation does not r
equire on-line optimization. Necessary conditions for stability of the
closed-loop system under the constrained dynamic control laws are giv
en. The connections between (a) the developed control laws and (b) the
model state feedback control;and the modified internal model control-
are established. The application and performance of the derived contro
llers are demonstrated by numerical simulations of chemical and bioche
mical reactor examples. (C) 1997 Elsevier Science Ltd.