Reinforcement Learning Adaptive PID Controller for an Under-actuated Robot Arm

Authors

  • Adel Akbarimajd Univeristy of Mohaghegh Ardabili

Keywords:

Robot manipulator, Under-actuated mechanism, Adaptive PID controller, Reinforcement learning

Abstract

Abstract: An adaptive PID controller is used to control of a two degrees of freedom under actuated manipulator. An actor-critic based reinforcement learning is employed for tuning of parameters of the adaptive PID controller. Reinforcement learning is an unsupervised scheme wherein no reference exists to which convergence of algorithm is anticipated. Thus, it is appropriate for real time applications. Controller structure and learning equations as well as update rules are provided. Simulations are performed in SIMULINK and performance of the controller is compared with NARMA-L2 controller. The results verified good performance of the controller in tracking and disturbance rejection tests.

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Author Biography

Adel Akbarimajd, Univeristy of Mohaghegh Ardabili

Assisstant Professor at Faculty of Electrical Engineering

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Published

27-10-2015

How to Cite

Akbarimajd, A. (2015). Reinforcement Learning Adaptive PID Controller for an Under-actuated Robot Arm. International Journal of Integrated Engineering, 7(2). Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/895

Issue

Section

Issue on Mechanical, Materials and Manufacturing Engineering