Measurement and calibration of rotor/touchdown bearing contact in active magnetic bearing systems

Saket, Fawaz Y.; Şahinkaya, M. Necip; Keogh, Patrick

doi:10.1016/j.ymssp.2018.12.005

Cited by 15 publications

(1 citation statement)

References 27 publications

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“…There are many nonlinear systems in the real world. For example, chaotic systems (Li et al, 2017; Liu et al, 2019; Shen and Li, 2017; Zhao et al, 2019), bearing systems (Cao et al, 2019; Jin et al, 2019; Saket et al, 2019), and so on (Liu and Tong, 2016). Therefore, the controller design for the nonlinear systems is an important topic.…”

Section: Introductionmentioning

confidence: 99%

Robust sliding model control-based adaptive tracker for a class of nonlinear systems with input nonlinearities and uncertainties

Fang

Tsai

Yan

et al. 2020

Transactions of the Institute of Measurement and Control

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A robust adaptive tracker is newly proposed for a class of nonlinear systems with input nonlinearities and uncertainties. Because the upper bounds of input nonlinearities and uncertainties are difficult to be acquired, the adaptive control integrated with sliding mode control (SMC) and radial basis function neural network (RBFNN) are utilized to cope with these undesired problems and effectively complete the robust tracker design. The main contributions are concluded as follows: (1) new sufficient conditions are obtained such that the proposed adaptive control laws can avoid overestimation; (2) A smooth [Formula: see text] function is introduced to eliminate the undesired chattering phenomenon in the traditional SMC systems; (3) A robust tracker is proposed such that the controlled system outputs can robustly track the pre-specified trajectories directly, even when subjected to unknown input nonlinearities and uncertainties. Finally, the numerical simulation results are illustrated to verify the proposed approach.

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