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

Adel Akbarimajd


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.


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

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Copyright (c) 2016 International Journal of Integrated Engineering

Copyright International Journal of Integrated Engineering (IJIE) 2013.

ISSN : 2229-838X

e-ISSN : 2600-7916

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