Active Model-Based Control for Pneumatic Artificial Muscle

In this paper, an active model-based control scheme is developed for the pneumatic artificial muscle (PAM), to compensate for the uncertainties in the dynamics model of the PAM. First, a simplified three-element model with respect to a specific range of pressure is formulated as the reference model. Second, a Kalman filter is adopted to actively estimate the errors involved in the reference model, especially while the PAM was working at the pressure outside the specific range where the reference model was built. Finally, a compensation control is proposed using the estimated errors to reject the modeling errors and improve the performance of the PAM. Experiments are conducted on a one degree-of-freedom testbed actuated by the PAM. The experimental results with and without the active-model-based compensation are presented and compared to demonstrate the improvements of the proposed scheme.