Journal of Artificial Intelligence and Digital Economy https://www.journal.antispublisher.id/index.php/JAIDE <p><strong><em>Journal of Artificial Intelligence and Digital Economy</em></strong> - is dedicated to the rapid dissemination of important research results to the global artificial intelligence (AI) community and digital economy. It is an open-access, community-focused journal publishing research covering all aspects of artificial intelligence in economical theory and digital application. The journal’s scope encompasses all areas of digitalization, economics, and finance with the comparison of AI, including agents and multi-agent systems, automated reasoning, constraint processing and search, knowledge representation, machine learning, natural language, planning and scheduling, robotics and vision, and uncertainty in AI.<br /><br /></p> en-US admin@antispublisher.com (Mochamad Nashrullah) Nashrul.id@gmail.com (Mochamad Nashrullah) Thu, 19 Mar 2026 02:20:54 +0000 OJS 3.3.0.13 http://blogs.law.harvard.edu/tech/rss 60 DESIGN AND CONTROL OF A MULTI-DOF FLEXIBLE ROBOTIC ARM USING ADAPTIVE FUZZY LOGIC CONTROL FOR PRECISION GRASPING TASKS https://www.journal.antispublisher.id/index.php/JAIDE/article/view/1722 <p><strong><em>Objective:</em></strong><em> Flexible robots pose a great challenge when partial manipulation is to be performed under unstructured environments. This paper deals with the issue of specific endpoint control and vibration cancellation of a multi-degree-of-freedom (DOF) tendon-driven flexible arm. The main shortcoming of standard controllers like PID is that they cannot respond to the nonlinearities, time-varying dynamics, and external disturbances inherent in the system and this is a major limitation on understanding reliability. <strong>Method:</strong> The methodology consists of detailed mechanical design through CAD/FEA, kinematic and dynamic modulization through a piecewise constant curvature approximation and synthesis of an online adaptive fuzzy inference system. The proposed system is tested with the help of simulation and physical testing. It uses a hierarchical control architecture, which means that a high-level AFLC is in charge of the positioning of endpoints and vibration damping, with low-level PID controllers being used to ensure proper actuator tracking. <strong>Results:</strong> The major findings show that the trajectory tracking error (RMSE) decreased by 55.6 %, the amplitude of vibrations reduced by 70 % and the grasping success rates increased significantly, 40 % (PID) to 75 % (AFLC) with a fine stress ball. The settling time and the overshoot are also reduced by 45.2% and 61.6% respectively to the baseline PID controller by the AFLC. <strong>Novelty:</strong> The greatest value of this work is that an integrated framework was developed and tested with the purpose of combining a new mechanical design and Adaptive Fuzzy Logic Controller (AFLC).</em></p> Nabeel Muhamed Akram Samad Copyright (c) 2026 Nabeel Muhamed Akram Samad https://creativecommons.org/licenses/by/4.0 https://www.journal.antispublisher.id/index.php/JAIDE/article/view/1722 Sat, 28 Feb 2026 00:00:00 +0000