A predictive robust cascade position-torque control strategy for Pneumatic Artificial Muscles

A robust cascade strategy is proposed and tested on an electropneumatic testbed for parallel robotic applications. It is applied on Pneumatic Artificial Muscles (PAMs). Nonlinear models are developed and presented. By specifying the pressure average between the two muscles, it is possible to control the torque by controlling the pressure in each muscle. A constrained LMI based H ∞ controller is synthesized for the pressure inner loop. A computed torque is applied on the torque loop and a Generalized Predictive Controller (GPC) controller is then applied to control position of the muscles. Experimental results show the feasibility of the control strategy and good performances in terms of robustness and dynamic tracking.