Journal
MATHEMATICS
Volume 10, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/math10030339
Keywords
sliding mode control; control of robots; fault-tolerant control; adaptive law; redundant control
Categories
Funding
- Science and Technology Foundation of Guangdong Province [2019B090910001, 2021A0101180005]
- National Natural Science Foundation of China [61941301, 61803090, 11771102, 61573108]
- China Postdoctoral Science Foundation [2018M633353]
- Special Program for Key Field of Guangdong Colleges [2019KZDZX1037]
- Natural Science Foundation of Guangdong Province [2016A030313715, 2016A030310237, 2016A030313018, 2019A1515012109]
- Scientific and Technical Supporting Programs of Sichuan Province [2017GZ0391,2019YFG0352, 2017GZ0392]
Ask authors/readers for more resources
This paper presents a new adaptive sliding mode controller for robot manipulators with unknown disturbances and system failures, achieving asymptotic tracking and avoiding singularity problems.
This paper presents a novel adaptive sliding mode controller for a class of robot manipulators with unknown disturbances and system failures, which can well achieve the asymptotic tracking, and avoid some possible singularity problems. A new virtual controller is designed such that the chosen Lyapunov function can be transformed into a non-Lipschitz function, based on which, the system states can arrive at the specified sliding surface within a finite time regardless of the existence of system failures/faults. By fusing an integral fast terminal nonsingular SMC and a robust adaptive technique, the tracking error can be steered into a preset range in a set time and some possible singularity problems are avoided elegantly. With our proposed scheme, the loss coefficient is well estimated, and the stability of the system can be guaranteed even in the presence of the total loss of actuator outputs. The experiment and simulation results are presented to illustrate the effectiveness of the proposed control scheme.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available