Uncalibrated sliding mode visual servoing of uncertain robot manipulators

2003 ◽  
Author(s):  
Parra-Vega ◽  
J.D. Fierro-Rojas ◽  
A. Espinosa-Romero
Keyword(s):  
Visual Servoing ◽  
Sliding Mode ◽  
Robot Manipulators ◽  
Uncertain Robot

Adaptive visual servoing scheme free of image velocity measurement for uncertain robot manipulators

Automatica ◽  
2013 ◽  
Vol 49 (5) ◽  
pp. 1304-1309 ◽  
Author(s):  
Fernando Lizarralde ◽  
Antonio C. Leite ◽  
Liu Hsu ◽  
Ramon R. Costa
Keyword(s):  
Velocity Measurement ◽  
Visual Servoing ◽  
Robot Manipulators ◽  
Image Velocity ◽  
Uncertain Robot

scholarly journals Fault Diagnosis and Fault-Tolerant Control of Uncertain Robot Manipulators Using High-Order Sliding Mode

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Mien Van ◽  
Pasquale Franciosa ◽  
Dariusz Ceglarek
Keyword(s):  
Fault Diagnosis ◽  
Velocity Measurement ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Fault Tolerant Control ◽  
High Order ◽  
Component Faults ◽  
Uncertain Robot

A robust fault diagnosis and fault-tolerant control (FTC) system for uncertain robot manipulators without joint velocity measurement is presented. The actuator faults and robot manipulator component faults are considered. The proposed scheme is designed via an active fault-tolerant control strategy by combining a fault diagnosis scheme based on a super-twisting third-order sliding mode (STW-TOSM) observer with a robust super-twisting second-order sliding mode (STW-SOSM) controller. Compared to the existing FTC methods, the proposed FTC method can accommodate not only faults but also uncertainties, and it does not require a velocity measurement. In addition, because the proposed scheme is designed based on the high-order sliding mode (HOSM) observer/controller strategy, it exhibits fast convergence, high accuracy, and less chattering. Finally, computer simulation results for a PUMA560 robot are obtained to verify the effectiveness of the proposed strategy.

scholarly journals Fixed-Time Sliding Mode Control for Uncertain Robot Manipulators

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 149750-149763 ◽  
Author(s):  
Liyin Zhang ◽  
Youming Wang ◽  
Yinlong Hou ◽  
Hong Li
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Robot Manipulators ◽  
Fixed Time ◽  
Mode Control ◽  
Uncertain Robot

Robust fault-tolerant control for uncertain robot manipulators based on adaptive quasi-continuous high-order sliding mode and neural network

2015 ◽  
Vol 229 (8) ◽  
pp. 1425-1446 ◽  
Author(s):  
Mien Van ◽  
Hee-Jun Kang
Keyword(s):  
Neural Network ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Robot Manipulators ◽  
Fault Tolerant Control ◽  
Stability And Convergence ◽  
Fault Estimation ◽  
The Neural Network ◽  
Fault Information ◽  
Uncertain Robot

This paper investigates a robust fault-tolerant control scheme for uncertain robot manipulators. The proposed scheme is designed via active fault-tolerant control method by combining a fault estimation scheme with a novel robust adaptive quasi-continuous second-order sliding mode (AQC2S) controller, so as to accommodate not only system failures but also uncertainties. First, a neural network based fault estimation is designed to online approximate the unknown uncertainties and faults. The estimated uncertainty and fault information are then used to compensate in advance for the effects of uncertainties in fault-free operation and both uncertainties and faults in fault operation. To eliminate the neural network compensation error, QC2S with adaptation gain, named as adaptive QC2S (AQC2S), is proposed. By integrating the advantages of the neural network observer and the AQC2S controller, the integrated scheme has a good capability to accommodate both the uncertainties and faults with chattering-free, higher position tracking accuracy, and no requirement of prior knowledge of the fault information. The stability and convergence of the proposed fault-tolerant control system is proved theoretically. Simulation results for a PUMA560 robot demonstrate the effectiveness of the proposed algorithm.

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