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 An Adaptive Integral Sliding Mode Tracking Control for Robotic Manipulators
Tác giả hoặc Nhóm tác giả: Anh Tuan Vo, Hee-Jun Kang and Tien Dung Le
Nơi đăng: ISCSIC 2019: Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control; Số: Article No.: 41, September;Từ->đến trang: 1-6;Năm: 2019
Lĩnh vực: Kỹ thuật; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
This paper proposes an adaptive integral sliding mode tracking control for robotic manipulators. Our proposed control method is developed based on the benefits of both integral sliding mode control and adaptive control, such as high robustness, high accuracy, and estimation ability. In this paper, an integral sliding mode controller is designed with the elimination of the reaching stage to provide better trajectory tracking accuracy and to stabilize the closed-loop system. To reduce the computation complexity, an adaptive controller with only one simple adaptive law is used to estimate the upper-bound values of the lumped model uncertainties. As a result, the requirement of their prior knowledge is eliminated and then decrease the computation cost. Consequently, this controller provides better tracking accuracy and handles the dynamic uncertainties and external disturbances more strongly. The system global stability of the controller is guaranteed by using Lyapunov criteria. Finally, the effectiveness of the proposed control method is tested by computer simulation for a PUMA560 robotic manipulator.
ABSTRACT
This paper proposes an adaptive integral sliding mode tracking control for robotic manipulators. Our proposed control method is developed based on the benefits of both integral sliding mode control and adaptive control, such as high robustness, high accuracy, and estimation ability. In this paper, an integral sliding mode controller is designed with the elimination of the reaching stage to provide better trajectory tracking accuracy and to stabilize the closed-loop system. To reduce the computation complexity, an adaptive controller with only one simple adaptive law is used to estimate the upper-bound values of the lumped model uncertainties. As a result, the requirement of their prior knowledge is eliminated and then decrease the computation cost. Consequently, this controller provides better tracking accuracy and handles the dynamic uncertainties and external disturbances more strongly. The system global stability of the controller is guaranteed by using Lyapunov criteria. Finally, the effectiveness of the proposed control method is tested by computer simulation for a PUMA560 robotic manipulator.
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