Fuzzy Torque Control of the Bionic Flexible Manipulator Actuated by Pneumatic Muscle Actuators

Abstract A bionic flexible manipulator driven by pneumatic muscle actuator (PMA) can better reflect the flexibility of the mechanism. Current research on PMA mainly focuses on the modeling and control strategy of the pneumatic manipulator system. Compared with traditional electro-hydraulic actuators...

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Bibliographic Details
Main Authors: Kai Liu, Yining Chen, Jiaqi Xu, Yang Wu, Yonghua Lu, Dongbiao Zhao
Format: Article
Language:English
Published: SpringerOpen 2019-10-01
Series:Chinese Journal of Mechanical Engineering
Subjects:
Online Access:http://link.springer.com/article/10.1186/s10033-019-0394-y
Description
Summary:Abstract A bionic flexible manipulator driven by pneumatic muscle actuator (PMA) can better reflect the flexibility of the mechanism. Current research on PMA mainly focuses on the modeling and control strategy of the pneumatic manipulator system. Compared with traditional electro-hydraulic actuators, the structure of PMA is simple but possesses strong nonlinearity and flexibility, which leads to the difficulty in improving the control accuracy. In this paper, the configuration design of a bionic flexible manipulator is performed by human physiological map, the kinematic model of the mechanism is established, and the dynamics is analyzed by Lagrange method. A fuzzy torque control algorithm is designed based on the computed torque method, where the fuzzy control theory is applied. The hardware experimental system is established. Through the co-simulation contrast test on MATLAB and ADAMS, it is found that the fuzzy torque control algorithm has better tracking performance and higher tracking accuracy than the computed torque method, and is applied to the entity control test. The experimental results show that the fuzzy torque algorithm can better control the trajectory tracking movement of the bionic flexible manipulator. This research proposes a fuzzy torque control algorithm which can compensate the error more effectively, and possesses the preferred trajectory tracking performance.
ISSN:1000-9345
2192-8258