Mohammad Bahari, Alvaro Paz, Mehdi Heydari Shahna, Jouni Mattila
{"title":"System-Level Efficient Performance of EMLA-Driven Heavy-Duty Manipulators via Bilevel Optimization Framework with a Leader--Follower Scenario","authors":"Mohammad Bahari, Alvaro Paz, Mehdi Heydari Shahna, Jouni Mattila","doi":"arxiv-2409.11849","DOIUrl":null,"url":null,"abstract":"The global push for sustainability and energy efficiency is driving\nsignificant advancements across various industries, including the development\nof electrified solutions for heavy-duty mobile manipulators (HDMMs).\nElectromechanical linear actuators (EMLAs), powered by permanent magnet\nsynchronous motors, present an all-electric alternative to traditional internal\ncombustion engine (ICE)-powered hydraulic actuators, offering a promising path\ntoward an eco-friendly future for HDMMs. However, the limited operational range\nof electrified HDMMs, closely tied to battery capacity, highlights the need to\nfully exploit the potential of EMLAs that driving the manipulators. This goal\nis contingent upon a deep understanding of the harmonious interplay between\nEMLA mechanisms and the dynamic behavior of heavy-duty manipulators. To this\nend, this paper introduces a bilevel multi-objective optimization framework,\nconceptualizing the EMLA-actuated manipulator of an electrified HDMM as a\nleader--follower scenario. At the leader level, the optimization algorithm\nmaximizes EMLA efficiency by considering electrical and mechanical constraints,\nwhile the follower level optimizes manipulator motion through a trajectory\nreference generator that adheres to manipulator limits. This optimization\napproach ensures that the system operates with a synergistic trade-off between\nthe most efficient operating region of the actuation system, achieving a total\nefficiency of 70.3\\%, and high manipulator performance. Furthermore, to\ncomplement this framework and ensure precise tracking of the generated optimal\ntrajectories, a robust, adaptive, subsystem-based control strategy is developed\nwith accurate control and exponential stability. The proposed methodologies are\nvalidated on a three-degrees-of-freedom manipulator, demonstrating significant\nefficiency improvements while maintaining high-performance operation.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.11849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The global push for sustainability and energy efficiency is driving
significant advancements across various industries, including the development
of electrified solutions for heavy-duty mobile manipulators (HDMMs).
Electromechanical linear actuators (EMLAs), powered by permanent magnet
synchronous motors, present an all-electric alternative to traditional internal
combustion engine (ICE)-powered hydraulic actuators, offering a promising path
toward an eco-friendly future for HDMMs. However, the limited operational range
of electrified HDMMs, closely tied to battery capacity, highlights the need to
fully exploit the potential of EMLAs that driving the manipulators. This goal
is contingent upon a deep understanding of the harmonious interplay between
EMLA mechanisms and the dynamic behavior of heavy-duty manipulators. To this
end, this paper introduces a bilevel multi-objective optimization framework,
conceptualizing the EMLA-actuated manipulator of an electrified HDMM as a
leader--follower scenario. At the leader level, the optimization algorithm
maximizes EMLA efficiency by considering electrical and mechanical constraints,
while the follower level optimizes manipulator motion through a trajectory
reference generator that adheres to manipulator limits. This optimization
approach ensures that the system operates with a synergistic trade-off between
the most efficient operating region of the actuation system, achieving a total
efficiency of 70.3\%, and high manipulator performance. Furthermore, to
complement this framework and ensure precise tracking of the generated optimal
trajectories, a robust, adaptive, subsystem-based control strategy is developed
with accurate control and exponential stability. The proposed methodologies are
validated on a three-degrees-of-freedom manipulator, demonstrating significant
efficiency improvements while maintaining high-performance operation.