Polynomial functions about inputs or states are added in the state space model, and the polynomial functions are used to denote the nonlinear factors. To identify every system matrix in the polynomial nonlinear state space model, each system matrix is vectorized as an unknown parameter vector, and two parallel distribution algorithms are applied in unconstrained or constrained conditions respectively. When some state equation equalities are deemed as the constrained conditions, the new optimization variables include the state instants and the unknown parameter vector which is consisted by all system matrices. These optimization variables are identified by using the parallel distribution algorithm, and the whole process about the parallel distribution algorithm are given explicitly. Finally, the simulation example is used to illustrate the effectiveness of the proposed parallel distribution algorithm.