This paper delves into the intricate mechanisms underlying the establishment and control of force feedback models within the manipulation loading system. PID control is employed to mitigate interference effects, while BP neural networks are utilized to identify and compensate for uncertain parameters in multi-degree-of-freedom actuators. Additionally, this paper explores the force control simulation of the system. The simulation results show that key issues such as suppressing interference and compensating uncertain parameters have been well resolved.