Adaptive predictive control of a novel shape memory alloy rod actuator

Abstract

Shape memory alloys are among the highly applicable smart materials that have recently appealed to scientists from various fields of study. In this article, a novel shape memory alloy actuator, in the form of a rod, is introduced, and an adaptive model predictive control system is designed for position control of the developed actuator. The need for such an advanced control system emanates from the fact that modeling and controlling of shape memory alloy actuators are thwarted by their hysteresis nonlinearity, dilatory response, and high dependence on environmental conditions. Real-time identification and dynamic parameter estimation of the model are addressed according to orthogonal Laguerre functions and recursive least square algorithm. In the end, the designed control system is implemented on the experimental setup of the fabricated shape memory alloy actuator. It is observed that the designed control system successfully tracks the variable step and sinusoidal control references with startling accuracy of ±1 μm.