An Adaptive Robust Hybrid Force/Position Control for Robot Manipulators System subject to Mismatched and matched Disturbances

A novel adaptive robust hybrid force/position control (ARHFPC) strategy is proposed for robot manipulator systems subject to dynamic uncertainties and unknown matched and mismatched disturbances under input saturation. First, the position controller is designed based on the backstepping approach. Th...

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Published inIEEE access Vol. 12; p. 1
Main Authors Lv, Chengxing, Chen, Gang, Zhao, Huamin, Chen, Jian, Yu, Haisheng
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.01.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract A novel adaptive robust hybrid force/position control (ARHFPC) strategy is proposed for robot manipulator systems subject to dynamic uncertainties and unknown matched and mismatched disturbances under input saturation. First, the position controller is designed based on the backstepping approach. The first-order low-pass filter and the auxiliary dynamic system are synthesized into the controller to overcome the complex derivative operation of virtual control and handle the effect of input saturation, respectively. Radial basis function neural networks (RBFNNs) are utilized to approximate the dynamic uncertainties and matched disturbances. Then, a disturbance observer is designed for the mismatched disturbances. To enhance control accuracy of the interaction force between the end-effector and the external environment, a fuzzy proportional-integral (FPI) control scheme is presented. Theoretical analysis proves that all signals in the closed-loop control system of robot manipulators are locally uniformly ultimately bounded (UUB). Simulation results demonstrate the effectiveness and robustness of the proposed control scheme.
AbstractList A novel adaptive robust hybrid force/position control (ARHFPC) strategy is proposed for robot manipulator systems subject to dynamic uncertainties and unknown matched and mismatched disturbances under input saturation. First, the position controller is designed based on the backstepping approach. The first-order low-pass filter and the auxiliary dynamic system are synthesized into the controller to overcome the complex derivative operation of virtual control and handle the effect of input saturation, respectively. Radial basis function neural networks (RBFNNs) are utilized to approximate the dynamic uncertainties and matched disturbances. Then, a disturbance observer is designed for the mismatched disturbances. To enhance control accuracy of the interaction force between the end-effector and the external environment, a fuzzy proportional-integral (FPI) control scheme is presented. Theoretical analysis proves that all signals in the closed-loop control system of robot manipulators are locally uniformly ultimately bounded (UUB). Simulation results demonstrate the effectiveness and robustness of the proposed control scheme.
Author Yu, Haisheng
Lv, Chengxing
Chen, Jian
Zhao, Huamin
Chen, Gang
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Snippet A novel adaptive robust hybrid force/position control (ARHFPC) strategy is proposed for robot manipulator systems subject to dynamic uncertainties and unknown...
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SubjectTerms Auxiliary Dynamic System
Backstepping
Closed loops
Control systems design
Controllers
Disturbance observers
Dynamical systems
End effectors
Feedback control
Force
Fuzzy control
Input Saturation
Low pass filters
Manipulator dynamics
Manipulators
Mismatched Disturbances Observer
Neural networks
Observers
Position control
Proportional integral
Radial basis function
Robot arms
Robot control
Robot Manipulators
Robot motion
Robots
Robust control
Uncertainty
Vectors
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Title An Adaptive Robust Hybrid Force/Position Control for Robot Manipulators System subject to Mismatched and matched Disturbances
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