DESIGN AND CONTROL OF A MULTI-DOF FLEXIBLE ROBOTIC ARM USING ADAPTIVE FUZZY LOGIC CONTROL FOR PRECISION GRASPING TASKS - Nabeel Muhamed Akram Samad (Journal of Artificial Intelligence and Digital Economy, 2026)
Objective: 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. Method: 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. Results: 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. Novelty: 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).