Adaptive Barrier Control for Nonlinear Servomechanisms with Friction Compensation
Keyword(s):
This paper proposes an adaptive barrier controller for servomechanisms with friction compensation. A modified LuGre model is used to capture friction dynamics of servomechanisms. This model is incorporated into an augmented neural network (NN) to account for the unknown nonlinearities. Moreover, a barrier Lyapunov function (BLF) is utilized to each step in a backstepping design procedure. Then, a novel adaptive control method is well suggested to ensure that the full-state constraints are within the given boundary. The stability of the closed-loop control system is proved using Lyapunov stability theory. Comparative experiments on a turntable servomechanism confirm the effectiveness of the devised control method.
2013 ◽
Vol 464
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pp. 215-221
2012 ◽
Vol 203
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pp. 226-230
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2011 ◽
Vol 143-144
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pp. 350-354
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2014 ◽
Vol 631-632
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pp. 654-659
2016 ◽
Vol 25
(11)
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pp. 1650132
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2018 ◽
Vol 10
(6)
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pp. 168781401878284