A neural network combined with sliding mode controller for the two-wheel self-balancing robot
2021 ◽
Vol 10
(3)
◽
pp. 592
Keyword(s):
This article presents the sliding control method combined with the selfadjusting neural network to compensate for noise to improve the control system's quality for the two-wheel self-balancing robot. Firstly, the dynamic equations of the two-wheel self-balancing robot built by Euler–Lagrange is the basis for offering control laws with a neural network of noise compensation. After disturbance-compensating, the sliding mode controller is applied to control quickly the two-wheel self-balancing robot reached the desired position. The stability of the proposed system is proved based on the Lyapunov theory. Finally, the simulation results will confirm the effectiveness and correctness of the control method suggested by the authors.
2012 ◽
Vol 22
(3)
◽
pp. 315-342
◽
Keyword(s):
2018 ◽
Vol 10
(8)
◽
pp. 11-21
◽
2018 ◽
Vol 15
(6)
◽
pp. 172988141881151
2011 ◽
Vol 378-379
◽
pp. 521-524
2021 ◽
Vol 15
(1)
◽
pp. 109-122
Keyword(s):
2021 ◽
Vol 24
(1)
◽
pp. 14-20
2020 ◽
Vol 20
(3)
◽