Abstract
Pneumatic artificial muscle (PAM) is composed mainly of a weave and a rubber tube inside it. Because of its unique geometric structure and material properties, PAMs have the typical shortcomings of highly asymmetric nonlinear hysteresis systems. When PAMs is applied to different robot systems, the hysteresis output performance is affected by the amplitude and the frequency of the input signal and applied load. To eliminate the effect of hysteresis, compensation control based on the hysteresis inverse model is an effective solution. In this paper, firstly, the frequency dependence and the load dependence of the dynamic inverse hysteresis curve of PAM are analyzed based on the experimental data. Secondly, a hysteresis inverse compensator is proposed to describe the dynamic inverse hysteresis behavior of PAM, based on the good dynamic behavior approximation ability of the recurrent fuzzy neural network (RFNN) and the strong hysteresis modeling ability of the hysteresis operator. Finally, we conduct an open-loop hysteresis compensation control experimental on PAM, we find that the hysteresis compensation method designed in this paper has a good hysteresis compensation effect under different load conditions.
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