A novel eigenstructure assignment method is presented which trades exact closed loop eigenvalue location against an improvement in the associated closed loop eigenvector match against membership of a desired set via either constrained or unconstrained optimizations. The polynomial approach removes the dependence of the cost functions on the closed loop eigenvector by describing the allowable desired eigenvector subspace as a function of the eigenvalue location. A fixed-wing aircraft example is used to demonstrates the benefit of eigenvalue trade-off over basic projection.