ILC for a fast linear axis driven by pneumatic muscle actuators

Iterative learning control is a popular method for accurate trajectory tracking of systems that repeat the same motion many times. This paper presents two different approaches of iterative learning control for a novel linear axis. Its guided carriage is driven by a nonlinear mechanism consisting of two pulley tackles with a pair of pneumatic muscle actuators arranged at both sides. This innovative drive concept allows for an increased workspace as well as higher carriage velocities as compared to a direct actuation. The proposed control has a cascade structure. The internal pressure of each pneumatic muscle is controlled by a fast underlying control loop. Hence, the control design for the outer control loop can be simplified by considering these controlled muscle pressures as ideal control inputs. For the outer control loop a PID-type iterative learning control and, alternatively, a norm-optimal iterative learning control of the carriage position is proposed. Experimental results from an implementation on a test rig show an excellent control performance.