Robustness-Guaranteed Observer-Based Control Strategy with Modularity for Cleantech EMLA-Driven Heavy-Duty Robotic Manipulator

This paper introduces an innovative observer-based modular control strategy in a class of na-degree-of-freedom (DoF) fully electrified heavy-duty robotic manipulators (HDRMs) to 1) guarantee robustness in the presence of uncertainties and disturbances, 2) address the complexities arising from several interacting mechanisms, 3) ensure uniformly exponential sta- bility, and 4) enhance overall control performance. To begin, the dynamic model of HDRM actuation systems, which exploits the synergy between cleantech electromechanical linear actuators (EMLAs) and permanent magnet synchronous motors (PMSMs), is investigated. In addition, the reference trajectories of each joint are computed based on direct collocation with B-spline curves to extract the key kinematic and dynamic quantities of HDRMs. To guarantee robust tracking of the computed trajectories by the actual motion states, a novel control methodology, called robust subsystem-based adaptive (RSBA) control, is enhanced through an adaptive state observer. The RSBA control addresses inaccuracies inherent in motion, including modeling errors, non-triangular uncertainties, and both torque and voltage dis- turbances, to which the EMLA-driven HDRM is susceptible. Furthermore, this approach is presented in a unified generic equation format for all subsystems to mitigate the complexities of the overall control system. By applying the RSBA architecture, the uniformly exponential stability of the EMLA-driven HDRM is proven based on the Lyapunov stability theory. The proposed RSBA control performance is validated through simulations and experiments of the scrutinized PMSM-powered EMLA-actuated mechanisms. Note to Practitioners—Following strict global regulations, such as the 2015 Paris Agreement, there has been significant attention paid to the electrification trend. In this regard, the advancement of zero-emission electromechanical linear actuator technology has played a substantial role in developing fully electrified HDRMs. However, these systems are highly nonlinear and complex, comprising several interacting components, such as electric motors, reduction gearboxes, screw mechanisms, and Received 17 September 2024; revised 6 November 2024; accepted 17 December 2024. Date of publication 26 December 2024; date of current version 4 April 2025. This article was recommended for publication by Associate Editor T. Zhang and Editor B. Vogel-Heuser upon evaluation of the reviewers’ comments. This work was supported by the Business Finland Partnership Project Future All-Electric Rough Terrain Autonomous Mobile Manipulators under Grant 2334/31/2022. (Corresponding author: Mehdi Heydari Shahna.) The authors are with the Faculty of Engineering and Natural Sciences, Tampere University, 33100 Tampere, Finland (e-mail: mehdi.heydarishahna@tuni.fi; mohammad.bahari@tuni.fi; jouni.mattila@ tuni.fi). Digital Object Identifier 10.1109/TASE.2024.3520638 load-bearing structures. Each of these components is prone to adverse effects arising from inaccuracies in modeling equations, sensor readings, and torque or voltage disturbances. As a result, achieving high-performance control presents significant chal- lenges for engineers and necessitates computationally intensive approaches in practice. This paper presents a subsystem-based approach, enhanced by a robust state observer, to 1) miti- gate the impact of uncertainties and disturbances substantially, 2) alleviate the computational burden and complexity of the targeted system, 3) prove mathematical stability, and 4) offer highly accurate and fast tracking performance. The pro- posed approach employs the dynamic motion of the studied EMLA-actuated HDRM, decomposing it into distinct subsystems and introducing a unified generic equation control for all sub- systems. This modularity feature paves the way for researchers to extend the proposed approach to address other intricate applications.