Date: 2020
Type: Article
Recurrent neural network-based robust nonsingular sliding mode control with input saturation for a non-holonomic spherical robot
Institute of electrical and electronics engineers (IEEE) access, 2020, Vol. 8, pp. 188441-188453
CHEN, Shu-Bo, BEIGI, Alireza, YOUSEFPOUR, Amin, RAJAEE, Farhad, JAHANSHAHI, Hadi, BEKIROS, Stelios D., MARTINEZ, Raul Alcaraz, CHU, Yu-Ming, Recurrent neural network-based robust nonsingular sliding mode control with input saturation for a non-holonomic spherical robot, Institute of electrical and electronics engineers (IEEE) access, 2020, Vol. 8, pp. 188441-188453
- https://hdl.handle.net/1814/70179
Retrieved from Cadmus, EUI Research Repository
We develop a new robust control scheme for a non-holonomic spherical robot. To this end, the mathematical model of a pendulum driven non-holonomic spherical robot is first presented. Then, a recurrent neural network-based robust nonsingular sliding mode control is proposed for stabilization and tracking control of the system. The designed recurrent neural network is applied to approximate compound disturbances, including external interferences and dynamic uncertainties. Moreover, the controller is designed in a way that avoids the singularity problem in the system. Another advantage of the proposed scheme is its ability for tracking control while there exists control input saturation, which is a serious concern in robotic systems. Based on the Lyapunov theorem, the stability of the closed-loop system has also been confirmed. Lastly, the performance of the proposed control technique for the uncertain system in the presence of an external disturbance, unknown input saturation, and dynamic uncertainties has been investigated. Also, the proposed controller has been compared with a Fuzzy-PID one. Simulation results show the effectiveness and superiority of the developed control technique.
Additional information:
First published online: 13 October 2020
Cadmus permanent link: https://hdl.handle.net/1814/70179
Full-text via DOI: 10.1109/ACCESS.2020.3030775
ISSN: 2169-3536
Publisher: Institute of Electrical and Electronics Engineers