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All Journal IAES International Journal of Robotics and Automation (IJRA) Journal of Robotics and Control (JRC)
Addie Irawan
Universiti Malaysia Pahang (UMP)
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Interaction Motion Control on Tri-finger Pneumatic Grasper using Variable Convergence Rate Prescribed Performance Impedance Control with Pressure-based Force Estimator Irawan, Addie; Azahar, Mohd Iskandar Putra; Pebrianti, Dwi
Journal of Robotics and Control (JRC) Vol 3, No 5 (2022): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i5.16316

Abstract

Pneumatic robot is a fluid dynamic based robot system which possesses immense uncertainties and nonlinearities over its electrical driven counterpart. Requirement for dynamic motion handling further challenged the implemented control system on both aspects of interaction and compliance control. This study especially set to counter the unstable and inadaptable proportional motions of pneumatic robot grasper towards its environment through the employment of Variable Convergence Rate Prescribed Performance Impedance Control (VPPIC) with pressure-based force estimation (PFE). Impedance control was derived for a single finger of Tri-finger Pneumatic Grasper (TPG) robot, with improvement being subsequently made to the controller’s output by appropriation of formulated finite-time prescribed performance control. Produced responses from exerted pressure of the maneuvered pneumatic piston were then recorded via derived PEE with adherence to both dynamics and geometry of the designated finger. Validation of the proposed method was proceeded on both circumstances of human hand as a blockage and ping-pong ball as methodical representation of a fragile object. Developed findings confirmed relatively uniform force sensing ability for both proposed PEE and load sensor as equipped to the robot’s fingertip with respect to the experimented thrusting and holding of a human hand. Sensing capacity of the estimator has also advanced beyond the fingertip to enclose its finger in entirety. Whereas stable interaction control at negligible oscillation has been exhibited from VPPIC against the standard impedance control towards gentle and compression-free handling of fragile objects. Overall positional tracking of the finger, thus, justified VPPIC as a robust mechanism for smooth operation amid and succeed direct object interaction, notwithstanding its transcendence beyond boundaries of the prescribed performance constraint.     
Real-time control signal rectification and actuation mapping for robot joint control Irawan, Addie; Razali, Akhtar Razul; Amran, Aliza Che; Ahmad, Hamzah
IAES International Journal of Robotics and Automation (IJRA) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v15i1.pp43-51

Abstract

This paper presents the control signal rectification and actuation mapping (CSRAM) framework, developed to improve the reliability and precision of real-time robot joint control. The framework integrates three modules, namely the drive signal rectifier (DSR), the signal pole detector (SPD), and the rising/downstream detector (RDD), which ensure signal compatibility, dynamic mapping consistency, and directional stability during actuation. Unlike conventional control converters, CSRAM effectively compensates for nonlinearities, latency, and synchronization issues in closed-loop systems. Experimental validation using a hexapod-to-quadruped (Hexaquad) robot showed that the proposed method, when combined with an anti-windup PI controller, reduced steady-state error from 14% to below 1%, improved transient and settling times by 0.3 to 0.4 seconds, and decreased three-dimensional trajectory RMSE by 63.7%. These results confirm that CSRAM provides a low-complexity and computationally efficient preprocessing layer for improving real-time performance in multi-joint and legged robotic systems, with strong potential for adaptive and industrial robotic platforms.
Co-Authors Amran, Aliza Che Azahar, Mohd Iskandar Putra Hamzah Ahmad, Hamzah Pebrianti, Dwi Razali, Akhtar Razul