Dereje Shiferaw (PhD)Tsenat Abebe2025-07-302025-07-302025-05https://etd.aau.edu.et/handle/123456789/5869Robotic pick-and-place systems bring remarkable speed and precision to manufacturing lines. Adaptive control is one of the effective approaches for designing controllers for mechanical robot manipulators, particularly in addressing the nonlinearities and uncertainties inherent in robot dynamic models. When the robotic end-effector encounters varying masses and load conditions, the motion control directly affects the overall performance, stability, and speed of the robot. To address these challenges, this paper presents the design of a controller for a second-order system using a Model Reference Adaptive Control (MRAC) scheme, where the adaptive mechanism and controller design are based on the Lyapunov method. A Lyapunov candidate function is employed both to derive the adaptation law and to guarantee the stability of the system. The tracking error performance of the MRAC is demonstrated across all six joint positions of the PUMA 560 robot. For Joint 1, the error exhibits an initial peak magnitude of2×10 −5 rad under disturbance, settling to near-zero within 2 seconds, while the undisturbed error remains negligible. Similarly, Joint 2 shows a slightly lower peak error of1.8×10 −5 rad, with steady-state achieved in about 2.5 seconds. Joint 3 experiences a slightly higher peak error of2.2×10 −5 rad and takes 3 seconds to settle. Joint 4 exhibits the highest peak error of2.5×10 −5 rad, with a settling time of approximately 3.5 seconds, demonstrating the greatest sensitivity to disturbance among the joints. Joint 5 and Joint 6 show peak error magnitudes of2×10 −5 rad and2.3×10 −5 rad, respectively, both reaching steady-state within 3 secondsen-USAdaptive controlLyapunovMRACPuma 560 Robot Manipulator.Thesis