Existing works normally find the appropriate parameters using the collected data from vivo subjects23. However the experimental data are limited and may not be extended to different insects, or even different muscles on a single insect. Given the difference of the neural system between real and virtual insects, it is not of significance to follow the exact parameter values of real insects. Given the complicated model of nonlinear muscle, together with the parameters of neural system, we expect a high dimension of control space. It is challenging to reach an optimal solution for such optimization problem. In such circumstances, we propose the evolutionary algorithm to optimize the parameters of the controller and muscles simultaneously.