A trajectory optimization scheme based on the property of differential flat
ness is proposed in this paper. A dynamic optimization problem is transform
ed into a lower dimensional nonlinear programming problem through the use o
f flat outputs. This optimization approach is demonstrated in the repeated
optimization of nonlinear dynamic systems under feedback in an approach sim
ilar to nonlinear model predictive control. This approach is illustrated on
two examples involving biomass optimization and product optimization. Opti
mization under feedback is studied for the nominal problem and the case whe
re uncertainty is present. The proposed scheme is also used in conjunction
with a nonlinear Luenberger observer to generate the optimal trajectories u
nder parametric uncertainty. (C) 2001 Elsevier Science Ltd. All rights rese
rved.