Demonstration of self-sensing in Shape Memory Alloy actuated gripper

Abstract

This paper demonstrates the self-sensing behaviour of Shape Memory Alloys (SMAs) in controlling an SMA wire actuated gripper. High power-to-weight ratio, large recovery strain, low driving voltages and direct drive capability of SMA attracted considerable research attention. To make SMA more applicable to small scale robotic manipulations, its motion control using accurate self-sensing is a best alternative. The self-sensing algorithm uses sliding mode control (SMC) in this work. A self-sensing model is built by measuring the electrical resistance of SMA wire. The polyfit model facilitates to replace additional sensor and electronics for position feedback. Demonstration of the advantages gained from using self-sensing polyfit model is evident through stationary trajectory tracking control experiment. The method is accurate and precise in tracking, providing a scope for sensorless control by simplifying the control system. With the merits shown, we expect this technique can be utilized for SMA actuators in meso to micro scale applications. � 2013 IEEE.