Barrel-type structures are ubiquitous in industry and life. A novel construction platform of barrel-type structures is introduced, and it involves a multi-motor system. The synchronous control of multiple motors has great importance. To guarantee the high precision, high stability, and fast response for the collaborative control of multiple motors, this paper proposes a multi-motor cooperative control strategy. Firstly, a speed synchronization control structure between multiple permanent magnet synchronous motors (PMSM) is designed by way of the mean coupling control structure. Then, the conventional PID controller is improved by machine learning. Moreover, a radial basis function neural (RBF) network is introduced to the conventional PID algorithm for system identification processing, and the gradient descent algorithm is used for parameter updating. An improved variable speed integral term is introduced into the integral term of the conventional PID algorithm to eliminate the error as soon as possible. Finally, it is verified via numerical simulation experiments that show the multi-motor cooperative control strategy has high anti-interference ability and robustness.