System-Level Efficient Performance of EMLA-Driven Heavy-Duty Manipulators via Bilevel Optimization Framework with a Leader--Follower Scenario

Mohammad Bahari, Alvaro Paz, Mehdi Heydari Shahna, Jouni Mattila
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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.
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通过双层优化框架实现 EMLA 驱动的重型机械手的系统级高效性能(领导者--追随者方案
由永磁同步电机驱动的机电线性推杆(EMLAs)是传统内燃机(ICE)驱动的液压推杆的全电动替代品,为重型移动机械手(HDMMs)的环保未来提供了一条充满希望的道路。然而,电气化 HDMM 的工作范围有限,这与电池容量密切相关,因此需要充分挖掘驱动机械手的 EMLAs 的潜力。要实现这一目标,就必须深入了解 EMLAs 机制与重型机械手动态行为之间的和谐互动。为此,本文引入了一个双层多目标优化框架,将电动化重型机械的 EMLA 驱动机械手概念化为领导者-追随者情景。在领导者层面,优化算法通过考虑电气和机械约束,最大限度地提高 EMLA 的效率;而在跟随者层面,则通过轨迹参考生成器优化机械手的运动,使其遵守机械手的限制。这种优化方法可确保系统在执行系统最高效工作区域(总效率达到 70.3%)和机械手高性能之间进行协同权衡。此外,为了补充这一框架并确保精确跟踪生成的最优轨迹,还开发了一种基于子系统的稳健、自适应控制策略,该策略具有精确控制和指数稳定性。所提出的方法在一个三自由度操纵器上进行了验证,证明在保持高性能操作的同时显著提高了效率。
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