The static test platform of pneumatic artificial muscle was built，and a series of measurement tests were carried out under pressure of 0. 1 ～ 0. 8 MPa to analyze the characteristics of pneumatic artificial muscle． The mathematical model，which was built based on the theoretical model and test data，shows a high accuracy of solu-tion． In consideration of the influence of external load，gas pressure and system friction on the mathematical mod-el，a PID control strategy based on ＲBF network was designed with the fast learning ability of ＲBF network． Un-der the condition of external load F = 50 ～ 200 N，the dynamic test platform was built and a number of position control tests were implemented． The results show that the traditional PID control strategy can only achieve better control accuracy within a certain range of external loads，while the proposed strategy is able to adjust the PID pa-rameters adaptively． Moreover，the proposed PID control strategy has the advantages of higher response speed，shorter adjustment time and smaller overshoot，and it can better compensate the mathematical model error and a-chieve higher control accuracy．