Sensor Less Control Of Shape Memory Alloy Using Artificial Neural Network And Variable Structure Controller
Download Sensor Less Control Of Shape Memory Alloy Using Artificial Neural Network And Variable Structure Controller PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Sensor Less Control Of Shape Memory Alloy Using Artificial Neural Network And Variable Structure Controller book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Sensor-less Control of Shape Memory Alloy Using Artificial Neural Network and Variable Structure Controller
This thesis presents an accurate and robust method to determine the angular position of a rotary manipulator using artificial neural network (ANN). A bias type, single degree of freedom rotary manipulator actuated by shape memory alloy (SMA) is used. During the operation of rotary manipulator, the SMA actuator experiences a complex thermo-mechanical loading due to varying stress and temperature, causing the transformation temperature to shift. An ANN is developed to accurately estimate the manipulator position. The ANN estimated position is then used to control the rotary manipulator and track different reference signals using a modified variable structure controller. The results of ANN validation and position control are presented. A novel method for controlling SMA actuator is proposed where the desired position is converted to corresponding resistance value using an ANN. This desired resistance value is compared with actual resistance to control the rotary manipulator. The results for ANN validation and position control are also presented.