To address the issue of underactuation caused by passive buffers in a tether-driven microgravity simulation system， an active buffer control method based on Pneumatic Artificial Muscles （PAM） was proposed. Firstly， the tether-driven microgravity simulation system was analyzed for ground-based micro/low-gravity simulation. A block-structured nonlinear neural network modeling method to effectively overcome the highly nonlinear nature of PAM was introduced. Subsequently， the disturbances caused by the flexible interaction between the tether and the spacecraft was analyzed. Finally， a nonlinear model predictive tracking control approach was employed. Compared to traditional PID control methods， the proposed was introduced approach offers advantages such as simple parameter adjustment， excellent real-time tracking performance， and robust control performance in the presence of perturbations to the target inertia parameters of the unloading system. Experimental results demonstrate that the proposed method ensures tracking force error within 3% under various disturbances. The feasibility of the active buffer based on PAMs is confirmed experimentally， and the proposed control method achieves force-tracking control in the presence of flexural uncertainty.