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.
Highlights
The pneumatic muscle actuator (PMA) is a new pneumatic element with characteristics similar to biological muscles
The fuzzy torque controller is designed based on the fuzzy controller [22], and the application of computed torque method to test the trajectory tracking of the flexible manipulator is realized as well
The computed torque method can ensure the stability of the trajectory tracking of the manipulator, and is able to control each joint separately by closed-loop control system
Summary
The pneumatic muscle actuator (PMA) is a new pneumatic element with characteristics similar to biological muscles. Wang et al [19] established a cascade human elbow joint model driven by PMAs, and designed a fuzzy PI controller for positiontracking experiments to improve the control accuracy and verify the effectiveness of the fuzzy controller. Zhao et al [20] proposed a self-adaptive disturbance rejection control strategy to improve the control effects of the single-joint manipulator driven by PMAs, and effectively solve nonlinear problems of the manipulator control system. These control theories improve the control effect of the pneumatic system to some extent, there are still many limitations such as model dependence, poor anti-interference ability, poor control precision, nonlinearity and uncertainty of the system, and so on. The fuzzy torque controller is designed based on the fuzzy controller [22], and the application of computed torque method to test the trajectory tracking of the flexible manipulator is realized as well
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