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This technical note deals with the robust exact pole placement problem: pole placement algorithms that guarantee a small variation of the assigned poles against possible perturbations. The solution to this problem is related to the solvability of a Sylvester-like equation. Thus, the main issue is to compute a well-conditioned solution to this equation. Also, the best candidate solution must possess the minimal condition number, to reduce sensitivity to perturbation. This problem is cast as a global optimization under linear matrix inequality constraints, for which a numerical convergent algorithm is provided and compared with the most attractive methods in the literature.