Thông tin chung
  English
  Đề tài NC khoa học
  Bài báo, báo cáo khoa học
  Hướng dẫn Sau đại học
  Sách và giáo trình
  Các học phần và môn giảng dạy
  Giải thưởng khoa học, Phát minh, sáng chế
  Khen thưởng
  Thông tin khác
  Tài liệu tham khảo
  Hiệu chỉnh
 
Số người truy cập: 106,840,282

 Neural Integral Non-Singular Fast Terminal Synchronous Sliding Mode Control for Uncertain 3-DOF Parallel Robotic Manipulators
Tác giả hoặc Nhóm tác giả: Anh Tuan Vo, Hee-Jun Kang
Nơi đăng: IEEE Access, IEEE Xplore Digital Library; Số: Volume: 8, Issue:1;Từ->đến trang: 65383 - 65394;Năm: 2020
Lĩnh vực: Kỹ thuật; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
Robotics have been substituting humans increasingly and effectively to operate repeated, dangerous, heavy, complicated works in human life, production industry, and discovery missions. This work designs a Neural Integral Non-singular Fast Terminal Synchronous Sliding Mode Control (NINFTSSMC) approach for 3-DOF parallel robotic manipulators with uncertain dynamics, using synchronous nonlinear sliding surface, where this sliding surface is formed through the integration of the Synchronization Control (SC) and the Integral Non-singular Fast Terminal Sliding Mode Control (INFTSMC). Accordingly, position errors and synchronization errors quickly converge to the sliding surface at the same time. Next, a Feed-Forward Neural Network (FNN) is applied to estimate uncertain dynamics, whose novelty, compared to a classic FNN, is that they utilize a Non-singular Fast Terminal Sliding Mode (NFTSM) error filter to replace a classic error filter. Thanks to this procedure, the lumped uncertain dynamics are compensated more quickly and more accurately, thus, the malfunction in the reaching phase of state variables approaching the sliding surface is handled thoroughly. Finally, the control approach is designed for a robotic system to achieve the prescribed performance, obtaining rapid error convergence, robustness with uncertain dynamics, minimum chattering, synchronization, and high precision. The stability of the control loop is secured according to the Lyapunov theory. To test the robustness and confirm the effectiveness of the suggested controller for a 3-DOF parallel manipulator, computer simulations and performance comparisons are conducted.
ABSTRACT
Robotics have been substituting humans increasingly and effectively to operate repeated, dangerous, heavy, complicated works in human life, production industry, and discovery missions. This work designs a Neural Integral Non-singular Fast Terminal Synchronous Sliding Mode Control (NINFTSSMC) approach for 3-DOF parallel robotic manipulators with uncertain dynamics, using synchronous nonlinear sliding surface, where this sliding surface is formed through the integration of the Synchronization Control (SC) and the Integral Non-singular Fast Terminal Sliding Mode Control (INFTSMC). Accordingly, position errors and synchronization errors quickly converge to the sliding surface at the same time. Next, a Feed-Forward Neural Network (FNN) is applied to estimate uncertain dynamics, whose novelty, compared to a classic FNN, is that they utilize a Non-singular Fast Terminal Sliding Mode (NFTSM) error filter to replace a classic error filter. Thanks to this procedure, the lumped uncertain dynamics are compensated more quickly and more accurately, thus, the malfunction in the reaching phase of state variables approaching the sliding surface is handled thoroughly. Finally, the control approach is designed for a robotic system to achieve the prescribed performance, obtaining rapid error convergence, robustness with uncertain dynamics, minimum chattering, synchronization, and high precision. The stability of the control loop is secured according to the Lyapunov theory. To test the robustness and confirm the effectiveness of the suggested controller for a 3-DOF parallel manipulator, computer simulations and performance comparisons are conducted.
© Đại học Đà Nẵng
 
 
Địa chỉ: 41 Lê Duẩn Thành phố Đà Nẵng
Điện thoại: (84) 0236 3822 041 ; Email: dhdn@ac.udn.vn