Neural Network based Weighting Factor Selection of MPC for Optimal Battery and Load Management in MEA

Wang, Xin; Gao, Yuan; Atkin, Jason; Bozhko, Serhiy

Abstract

This paper presents a Neural Network (NN)-based weighting factor (WF) selection method for the multi-objective cost function in Model Predictive Control (MPC). MPC is adopted for scheduling the loads and charging/discharging the battery intelligently on More-Electric Aircraft (MEA) in a preferred manner. The decisions which are made while the MPC is running utilize a cost function which weights together different objectives (using WFs). The final overall evaluation is performed by considering various objectives with full knowledge of what happened throughout the whole operation, which are weighted together by utilising weights appropriate to the user. The WFs utilized by the MPC to get the best overall result will usually differ from the weights used in the final evaluation. A NN is trained to predict the effects of different combinations of WF values, facilitating optimisation to find the minimum evaluation index, i.e. the most suitable weighting factors for the applied MPC.

Citation

Wang, X., Gao, Y., Atkin, J., & Bozhko, S. (2020, November). Neural Network based Weighting Factor Selection of MPC for Optimal Battery and Load Management in MEA. Presented at 2020 23rd International Conference on Electrical Machines and Systems (ICEMS), Hamamatsu, Japan

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2020 23rd International Conference on Electrical Machines and Systems (ICEMS)
• Start Date: Nov 24, 2020
• End Date: Nov 27, 2020
• Acceptance Date: Jun 3, 2020
• Online Publication Date: Dec 22, 2020
• Publication Date: Dec 22, 2020
• Deposit Date: Mar 5, 2021
• Publicly Available Date: Mar 5, 2021
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 1763-1768
• Series Title: International Conference on Electrical Machines and Systems (ICEMS)
• Series ISSN: 2640-7841
• ISBN: 9781728189307
• DOI: https://doi.org/10.23919/icems50442.2020.9290968
• Public URL: https://nottingham-repository.worktribe.com/output/5368136
• Publisher URL: https://ieeexplore.ieee.org/document/9290968
• Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.