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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

TL;DR

The paper addresses the challenge of maximizing energy efficiency in all‑electric heavy‑duty mobile manipulators by coupling EMLA actuation with manipulator dynamics. It introduces a bilevel leader–follower optimization that jointly optimizes EMLA efficiency and manipulator trajectory under dynamic and kinematic constraints, paired with a robust adaptive modular control strategy to ensure exponential stability and precise tracking. The methodology integrates energy‑flow modeling of EMLAs, VDC‑based manipulator dynamics, direct collocation trajectory optimization, and a robust decomposed control scheme, validated on a 3‑DoF HDMM, achieving a total actuation efficiency of $70.3\%$ and clear improvements in joint efficiencies. The framework offers a practical path toward sustainable, electrified HDMMs with preserved performance, and provides modular, scalable control suitable for industrial deployment.

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.

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

TL;DR

The paper addresses the challenge of maximizing energy efficiency in all‑electric heavy‑duty mobile manipulators by coupling EMLA actuation with manipulator dynamics. It introduces a bilevel leader–follower optimization that jointly optimizes EMLA efficiency and manipulator trajectory under dynamic and kinematic constraints, paired with a robust adaptive modular control strategy to ensure exponential stability and precise tracking. The methodology integrates energy‑flow modeling of EMLAs, VDC‑based manipulator dynamics, direct collocation trajectory optimization, and a robust decomposed control scheme, validated on a 3‑DoF HDMM, achieving a total actuation efficiency of and clear improvements in joint efficiencies. The framework offers a practical path toward sustainable, electrified HDMMs with preserved performance, and provides modular, scalable control suitable for industrial deployment.

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.
Paper Structure (23 sections, 54 equations, 23 figures, 1 table)

This paper contains 23 sections, 54 equations, 23 figures, 1 table.

Table of Contents

  1. Introduction
  2. Background and Context
  3. Research Gap and Motivations of the Study
  4. Contributions, Methodology, and Structure of the Paper
  5. Energy Conversions and Losses of EMLAs
  6. Dynamic and State Space Model of an EMLA
  7. Kinematic and Dynamic Analysis of a Heavy-Duty Manipulator Structure
  8. Fundamental Concepts of VDC
  9. Mathematical Modeling of Heavy-Duty Manipulator
  10. Kinematics of the 3-DoF heavy-duty manipulator
  11. Dyanmics of the 3-DoF heavy-duty manipulator
  12. Trajectory Optimization for Dynamic Heavy-Duty Manipulator Motion
  13. Bilevel Multi-Objective Optimization Concept
  14. Problem Formulation with a Leader--Follower Scenario
  15. EMLA-Driven Robotic Manipulator Optimization
  16. ...and 8 more sections

Figures (23)

  • Figure 1: Motivations, key contributions, and benefits of the study
  • Figure 2: Schematic of the EMLA mechanism
  • Figure 3: Power flow and dissipation sources in an EMLA
  • Figure 4: Equivalent circuits of PMSM in $dq$ reference frame
  • Figure 5: Power flow and dissipation sources in an EMLA
  • ...and 18 more figures