Model Reference Adaptive Control (MRAC) of Robotic Manipulators using a Modified Output Error Method (MOEM)

1992 ◽  
pp. 143-150
Author(s):  
Ricky Y. J. Tam ◽  
Stelios C. A. Thomopoulos
1997 ◽  
Vol 30 (11) ◽  
pp. 335-340
Author(s):  
Masahiro Oya ◽  
Toshihiro Kobayashi ◽  
Shinichi Sagara

Actuators ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 89 ◽  
Author(s):  
Bin Wei

In this paper, the author presents the adaptive control design and stability analysis of robotic manipulators based on two main approaches, i.e., Lyapunov stability theory and hyperstability theory. For the Lyapunov approach, the author presents the adaptive control of a 2-DOF (degrees of freedom) robotic manipulator. Furthermore, the adaptive control technique and Lyapunov theory are subsequently applied to the end-effector motion control and force control, as in most cases, one only considers the motion control (e.g., position control, trajectory tracking). To make the robot interact with humans or the environment, force control must be considered as well to achieve a safe working environment. For the hyperstability approach, a control system is developed through integrating a PID (proportional–integral–derivative) control system and a model reference adaptive control (MRAC) system, and also the convergent behavior and characteristics under the situation of the PID system, model reference adaptive control system, and PID+MRAC control system are compared.


Author(s):  
Dan Zhang ◽  
Bin Wei

Motion control accuracy of robotic manipulators affects the overall robotic system performance. When the end-effector grasps different payloads, the joint motion of robotic manipulators will vary depending on the different payload masses. Traditional controllers have the problem of not being able to compensate the payload variation effect. Model reference adaptive control has been proposed to address the above problem. This paper discusses the model reference adaptive control of robotic manipulators initially raised by Roberto Horowitz and its associated development by other authors. A case study for a hybrid controller, which is derived from the model reference adaptive control system, is presented. Very few recent papers can be found in the area of model reference adaptive control of robotic manipulators, and this study can provide a guideline for future research in the direction of model reference adaptive control for robotic arms.


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