Model-Based, Self-Sensing Actuator System based on antagonistic SMA Wires

Thermal shape-memory-alloys (SMA) are a class of smart materials well known for their ability to recover their original shape after a deformation by heating them above a specific transition temperature. A remarkable feature of SMA wires is their self-sensing capability, potentially eliminating the need for external sensors by exploiting the change of electrical resistance in response to a change of length. In tensile tests and for SMA wires working against a simple spring load, the resistance-displacement curve can be described with good approximation by a linear relationship, allowing for resistance feedback to effectively achieve sensorless control. Challenges for SMA self-sensing arise when considering antagonistic systems, where a pronounced hysteresis is observed in the resistance-displacement characteristics. To deal with this issue, this work proposes a novel self-sensing method for antagonistic SMA actuators having a highly hysteretic resistancedisplacement behavior. An online hysteresis compensation scheme, based on the modified Prandtl-Ishlinskii model, is implemented and used to linearize the resistance-displacement characteristic. A lab setup which allows characterization of an antagonistic SMA system as well as implementation of self-sensing control architectures is also developed. Experimental results show how, when combined with a PI controller, the developed scheme permits to noticeably reduce the error in comparison to compensator-free self-sensing architectures.