Adaptive Control for Unknown payload Variations in Robotic Arms

The analysis of payload variation in the RRRT robot shows a progressive impact of increasing load on joint forces, positional accuracy, and overall system performance. With a 0.5 kg payload, gravity effects and joint torques are minimal, resulting in negligible elastic deformation, precise end-effector positioning, and smooth motion of the prismatic joint. Under these conditions, the robot operates efficiently with a large safety margin. Increasing the payload to 1.0 kg approximately doubles the gravitational load and associated joint torques. This causes moderate increases in joint stress, friction, and compliance, particularly at the distal revolute joints and the prismatic actuator. While a slight reduction in accuracy occurs, the robot remains stable and capable of continuous operation. At the maximum payload of 1.5 kg, gravity-induced forces become more pronounced. The 200 mm link length and 100 mm prismatic extension amplify axial and bending loads, resulting in reduced stiffness, increased positioning error, and higher actuator demands that bring the system closer to its design limits. The adaptive fractional-order controller effectively compensates for these dynamic variations across all tested payloads. Simulation results indicate controlled torque requirements, limited link deflection, minimal increase in settling time, and safe failure indices even under the heaviest load. The improved performance attributed to the inherent memory properties and adaptive gain features of fractional-order control, demonstrating its suitability for manipulators operating in environments with variable payloads.

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