Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Shahna, Mehdi Heydari"'
Deep reinforcement learning (DRL) is emerging as a promising method for adaptive robotic motion and complex task automation, effectively addressing the limitations of traditional control methods. However, ensuring safety throughout both the learning
Externí odkaz:
http://arxiv.org/abs/2410.20907
This paper introduces a novel model-free control strategy for a complex multi-stage gearbox electromechanical linear actuator (EMLA) system, driven by a permanent magnet synchronous motor (PMSM) with non-ideal ball screw characteristics. The proposed
Externí odkaz:
http://arxiv.org/abs/2409.12406
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
Externí odkaz:
http://arxiv.org/abs/2409.11849
Autor:
Shahna, Mehdi Heydari, Mattila, Jouni
To advance theoretical solutions and address limitations in modeling complex servo-driven actuation systems experiencing high non-linearity and load disturbances, this paper aims to design a practical model-free generic robust control (GRC) framework
Externí odkaz:
http://arxiv.org/abs/2409.11828
In-wheel drive (IWD) systems enhance the responsiveness, traction, and maintenance efficiency of vehicles by enabling each wheel to operate independently. This paper proposes a novel robust torque-observed valve-based control (RTOVC) framework to add
Externí odkaz:
http://arxiv.org/abs/2409.11823
In robotics, contemporary strategies are learning-based, characterized by a complex black-box nature and a lack of interpretability, which may pose challenges in ensuring stability and safety. To address these issues, we propose integrating a collisi
Externí odkaz:
http://arxiv.org/abs/2402.02551
Autor:
Shahna, Mehdi Heydari, Mattila, Jouni
This paper presents a novel auto-tuning subsystem-based fault-tolerant control (SBFC) system designed for robotic manipulator systems with n degrees of freedom (DoF). It initially proposes a novel model for joint torques, incorporating an actuator fa
Externí odkaz:
http://arxiv.org/abs/2311.15852
This paper introduces an innovative observer-based modular control strategy in a class of n_a-degree-of-freedom (DoF) fully electrified heavy-duty robotic manipulators (HDRMs) to (1) guarantee robustness in the presence of uncertainties and disturban
Externí odkaz:
http://arxiv.org/abs/2311.15843
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