Accurate position control of shape memory alloy actuators based on self sensing model

• 1、School of Electrical Engineering and Automation, Harbin Institute of Technology

Abstract：There has been a great demand for shape memory alloy actuators (SMAA) within the field of micro-actuator. However, the method of realizing position servo control by adding sensors to SMAA, which not only increases the volume, weight, and cost, but also fails to achieve the wide strain range of SMAA state detection and control, which hinders the development trend of SMAA miniaturization. The SMAA self-sensing control method can avoid the use of sensors to achieve position control by detecting resistance. However, the SMAA self-sensing model (resistance-strain model) has serious nonlinear hysteresis characteristics, which is difficult to realize the SMAA wide strain range self-sensing modeling and control. Therefore, a new wide strain range self-sensing modeling method by using a new material of SMA and improved the polynomial fitting self-sensing modeling method through multiple stable data one-time fitting methods are proposed in this paper. Furthermore, a new neural network PID accurate position control strategy is presented. The study describes the self-sensing characteristics and operAccurate Accurate Position Control of Shape Memory Alloy Actuator based Sensorless neural network PID controlPosition Control of Shape Memory Alloy Actuator based Sensorless neural network PID controlating principle of SMAA, comparison of self-sensing characteristics of conventional materials and new materials, design of neural network PID controller, and experimental results of the position servo tracking and the interference robustness detection.

Keywords： Shape memory alloy Self perception model Sensorless control Actuator