Abstract
A predictive control algorithm based on modified locally linear model tree (LOLIMOT) with merging is implemented to control of an electromagnetic suspension system. A self-construction LOLIMOT is used to predict the response of the plant in a future time interval. This modified algorithm could improve the accuracy with reduced computational times and fewer rules which is important in real-time input optimization. An evolutionary programming (EP) is used to determine the optimized control variables for a finite future time interval. This method is applied to an Electromagnetic Suspension system (EMS) and simulation results show the effectiveness of the proposed predictive control strategy.
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.
