Abstract
Abstract A trajectory optimization scheme based on the property of differential flatness is proposed in this paper. A dynamic optimization problem is transformed into a lower dimensional nonlinear programming problem through the use of flat outputs. This optimization approach is demonstrated in the repeated optimization of nonlinear dynamic systems under feedback in an approach similar to nonlinear model predictive control. This approach is illustrated on two examples involving biomass optimization and product optimization. Optimization under feedback is studied for the nominal problem and the case where uncertainty is present. The proposed scheme is also used in conjunction with a nonlinear Luenberger observer to generate the optimal trajectories under parametric uncertainty.
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