Abstract
In this paper, we propose a control method for a rotary crane system using neuro-controller (NC) optimized by real-coded genetic algorithm (GA). The rotary crane is known to be a nonholonomic system. We have been successful to suppress the load swing from an initial rotation angle using NC. However, the trained NC have low control performance with untrained angles. In this study, the evaluation function of GA is improved in order to control the load swing from multiple initial positions. The validity of the proposed NC is verified through computer simulation. Simulation results show that the proposed NC has good control performance and robustness with noise and fluctuation of the initial states.
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 callMore From: IEEJ Transactions on Electronics, Information and Systems
Disclaimer: 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.
