A novel control scheme for a shape memory alloy actuator

Abstract

Shape Memory Alloy actuators are commonly termed as smart materials because of its inherent ability to change shape with change in temperature. They have widespread applications in various fields. But due to its highly nonlinear operation, accurate control is difficult to achieve. In this brief, an adaptive neurofuzzy controller is proposed to control an SMA actuator. For the purpose of eliminating output noise and to estimate system states a Kalman filter was employed. From the simulation results it was verified that neurofuzzy control scheme and Kalman filter has successfully implemented.