Trajectory shaping for the minimization of state-variable estimation errors

A technique is devised for synthesizing nonlinear controls that optimally shape nominal trajectories with respect to state-variable estimation errors propagating along the nominal trajectory. Both the nonlinear process and the observations upon which the estimation is based are corrupted by Gaussian white noise. A numerical example is presented that demonstrates the pronounced coupling effect of the nominal trajectory upon the propagation of state-variable estimation errors. Numerous practical implications of this work are cited.