Friction effects are particularly critical for industrial robots, since they can induce large
positioning errors, stick-slip motions, and limit cycles. This paper offers a reasoned overview …

Major challenges of controlling human–robot collaboration (HRC)-oriented modular robot
manipulators (MRMs) include the estimation of human motion intention while cooperating …

Due to the limited computing and processing ability of modular robot manipulator (MRM)
components, such as sensors and controllers, event-triggered mechanisms are considered …

In this paper, a novel health indicator-based decentralized event-triggered optimal fault-
tolerant control method is proposed for modular robot manipulators (MRMs). First, the …

A major technical challenge in controlling modular and reconfigurable robots is associated
with the kinematics and dynamic model uncertainties caused by reconfiguration. In parallel …

An adaptive fuzzy backstep** optimal control method is developed for modular robot
manipulators (MRMs) via value iteration (VI). This paper adopts joint torque feedback (JTF) …

This work focuses on the development of a pressure-loop controller for a hybrid brake-by-
wire system, composed of a hydraulic link and an electro-mechanical actuator. Towards this …

Precise low speed motion control of a robot manipulator calls for precise position and
velocity measurement and joint friction compensation, as well as robustness and …

This study deals with a robust non-smooth non-linearity compensation scheme for the direct-
drive robot manipulator with an asymmetric deadzone, dynamic friction in joints and …

This paper presents a decentralized robust zero-sum optimal control approach for modular
robot manipulators (MRMs) in contact with uncertain environments based on the adaptive …