Adaptive Tracking Control for Dynamic Model Uncertainties of a 6-DOF Industrial Staubli Robot Manipulator Carrying Variable Payloads

This work introduces the design of an adaptive tracking control strategy for a 6-DOF Staubli TX2-60L industrial robot manipulator operating under dynamic model uncertainties caused by variable payloads. A complete kinematic and dynamic model of the robot is derived using Denavit–Hartenberg parameters and the Lagrangian formulation, respectively. To address the limitations of conventional control methods under payload variations, an adaptive controller is designed, which continuously updates its parameters based on real-time tracking errors. A Lyapunov stability analysis is conducted to rigorously establish that the closed-loop system guarantees convergent tracking errors and bounded internal states. Simulation studies with different payload scenarios, including no load, step load variation, and continuous load changes, show the performance of the proposed control strategy. The results confirm that the adaptive controller maintains precise trajectory tracking and robust stability despite significant model uncertainties, highlighting its suitability for industrial pick-and-place and high-precision automation tasks.