Identification and Control of Shape Memory Alloys

Abstract

In recent years, shape memory alloys have been used widely as actuators in microelectromechanical systems. Shape memory alloys have non-linear hysteresis behaviours and parameter uncertainties that include electrical properties such as resistance. These behavioural uncertainties limit the control accuracy of shape memory alloy actuators using mathematical models. In this article, a new method is proposed for force control of shape memory alloy spring actuators. An artificial neural network is used to identify and control the shape memory alloy actuator. The shape memory alloy spring under test is a product of the Toki Corporation; its coil diameter is 0.62 mm, the diameter of the wire is 0.15 mm, and this type of shape memory alloy actuator can produce 40 gf. The results obtained are verified by an experimental set-up, which is also used to train the artificial neural network as an identifier and a controller of the system.