We propose a deterministic identification method that involves a priori information characterized as moments of a transfer function. The moments are expressed in terms of the solution to a Sylvester matrix equation. The Sylvester equation is incorporated with a conventional subspace identification method, and a problem for moment-constrained subspace identification is formulated. Since the identification problem is in a class of nonlinear optimization problems, it cannot be efficiently solved in numerical computation. Application of a change-of-variable technique reduces the problem to least squares optimization, and the solution provides a state-space model that involves the prespecified moments. Finally, the effectiveness of the proposed method is illustrated in numerical simulations. (C) 2018 Elsevier Ltd. All rights reserved.