Loading...
Smooth residual generation for robust isolation of faults in manipulators using joint torque sensors
226 viewed

Smooth residual generation for robust isolation of faults in manipulators using joint torque sensors

Karami, S

Smooth residual generation for robust isolation of faults in manipulators using joint torque sensors

Karami, S ; Sharif University of Technology | 2019

226 Viewed
  1. Type of Document: Article
  2. DOI: 10.1109/CDC40024.2019.9030151
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2019
  4. Abstract:
  5. Reliability of model-based failure detection and isolation (FDI) methods depends on the amount of uncertainty in a system model. Recently, it has been shown that the use of joint torque sensing results in a simplified manipulator model that excludes hardly identifiable link dynamics and other nonlinearities. We present a geometric approach to fault detection and isolation (FDI) for robotic manipulators using joint torque sensor in presence of model uncertainty. A systematic procedure is introduced for representing a robotic system model using joint torque sensor being affine with respect to faults and disturbances. The proposed FDI filter has smooth dynamics with freely selectable functions and it does not require high gains or threshold adjustment for the FDI purpose. The paper focus on actuator and torque sensor faults which are more common in practical cases. No information on manipulator model or on amplitude of faults and their rate are used. Simulation examples on a 3-degrees of freedom manipulator is carried out to illustrate performance of the proposed FDI method. © 2019 IEEE
  6. Keywords:
  7. Fault detection ; Robotics ; Torque ; Torque meters ; Uncertainty analysis ; Failure detection and isolations ; Fault detection and isolation ; Geometric approaches ; Joint torque sensing ; Joint torque sensors ; Model uncertainties ; Robotic manipulators ; Threshold adjustments ; Manipulators
  8. Source: 58th IEEE Conference on Decision and Control, CDC 2019, 11 December 2019 through 13 December 2019 ; Volume 2019-December , 2019 , Pages 2922-2927 ; 07431546 (ISSN); 9781728113982 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/9030151