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Adaptive tracking control of multi-link robots actuated by pneumatic muscles with additive disturbances

Published online by Cambridge University Press:  26 October 2016

Tarapong Karnjanaparichat  and
Radom Pongvuthithum
Tarapong Karnjanaparichat
Affiliation:
Department of Mechanical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand
Radom Pongvuthithum*
Affiliation:
Department of Mechanical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand
*
*Corresponding author. E-mail: [email protected]
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Summary

In this paper, we study the problem of adaptive position tracking for a multi-link robot driven by two opposing pneumatic muscle groups with additive disturbances. In contrast to widely used sliding mode control methods, the proposed controller is continuous and able to prevent chattering. All physical parameters of the robot and the pneumatic muscles, including pneumatic muscle coefficients, link lengths and moments of inertia are unknown and can be time-varying and the unknown additive disturbances can be discontinuous. Under these conditions, we prove that closed-loop trajectories of all of the joint positions can track any C1 joint reference signal. The joint errors will be within a prescribed error bound in a finite time. The adaptive controller only uses the reference signal, not its derivative. The continuous adaptive gain is one-dimensional. Simulations including a two-link robot arm with friction and realistic muscle models are presented to demonstrate the robustness of the adaptive control under severe changes of the system parameters. In all simulations, the joint positions can track C1 trajectories and all errors are within the prescribed error bound in the same time frame, even though the muscle parameters are vastly different.

Keywords

Control of Robotic SystemsRobot DynamicsExoskeletonsAutomationSerial Manipulator Design and Kinematics
Type
Articles
Information
Robotica , Volume 35 , Issue 11 , November 2017 , pp. 2139 - 2156
Copyright
Copyright © Cambridge University Press 2016 

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