Abstract
The next-generation semiconductor lithography equipment needs a suitable actuator to meet the requirement of high-speed, high-acceleration and high-precision. Reluctance actuator, which has a unique property of small volume, low current and can produce great force, is a very suitable choice. One of the major application challenges of reluctance actuator is the hysteresis of the force, which has a nonlinear relationship with respect to the current and is directly related to the final accuracy in the nanometer range. Therefore, it is necessary to study the control method for the hysteresis in reluctance force. This paper proposes a hysteresis control configuration for the current-driven variable reluctance actuator with hysteresis using the adaptive multilayer neural network (MNN), which is used as a learning machine of hysteresis. The simulation results show that the proposed method is effective in overcoming the hysteresis.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
