Virtual environment simulations have gained great importance in the field of robotics by enabling the validation and optimization of control algorithms before their implementation on real platforms. However, the construction of accurate digital models is limited not only by the lack of detailed characterization of the components but also by the uncertainty introduced by the physics engine and the plugins used in the simulation. Unlike other works, which attempted to model each element of the robot in detail and rely on the physics engine to reproduce its behavior, this paper proposes a methodology based on model following. The proposed architecture forces the simulated robot to replicate the dynamics of the real robot without requiring exactly the same physical parameters. The experimental validation was carried out on two unmanned surface vehicle (USV) platforms with different dynamic parameters and, therefore, different responses to excitation signals, demonstrating that the proposed approach enables a drastic reduction in error. In particular, RMSE and MAE were reduced by more than 98%, with R2 values close to 1.0, demonstrating an almost perfect correspondence between the real and simulated dynamics.
