Adaptive control of system involving complex hysteretic nonlinearities: a generalised Prandtl–Ishlinskii modelling approach

Su, Cheng‐Kuan; Feng, Ying; Hong, Henry; Chen, Xinkai

doi:10.1080/00207170902736307

Cited by 42 publications

(46 citation statements)

References 27 publications

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“…In fact, application of MR damper in the vehicle suspension system has been reported in some literatures [10,[14][15][16]. According to magneto-rheological technology, the adjustment of the damping force can be realized by changing the input current.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive estimation and control of MR damper for semi-active suspension systems

Qianqian

Huang

et al. 2016

2016 35th Chinese Control Conference (CCC)

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Section: Introductionmentioning

confidence: 99%

“…In [17], a semi-active suspension with an LPV/ H ∞ control method was designed. In [15], an adaptive control method was designed to manage the complex hysteretic nonlinearities. However, the accurate online modeling of suspension system with MR damper deserves further investigation.…”

Section: Introductionmentioning

confidence: 99%

Adaptive estimation and control of MR damper for semi-active suspension systems

Qianqian

Huang

et al. 2016

2016 35th Chinese Control Conference (CCC)

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“…Based on the classical PI model, a few studies have presented different extensions of the classical PI model to describe asymmetric, saturated and rate-dependent hysteresis characteristics observed in some smart materials based actuators (Su et al, 2009;Zhang et al, 2013;Minorowicz et al, 2016). For example, the generalized Prandtl-Ishlinskii model (GPIM) being constructed by asymmetric hysteresis operator and modified Prandtl-Ishlinskii model (MPIM) being built by classical PI model combining with dead-zone operators are used to express the asymmetric and saturated hysteresis in magnetic shape memory alloys based actuators (Minorowicz et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…The hysteresis phenomena in magnetostrictive actuators have been widely investigated, including various modeling methods (Brokate and Sprekels, 1996;Kuhnen, 2013) and related control approaches (Chen and Hisayama, 2008;Li et al, 2014;Feng et al, 2008;Su et al, 2009) for mitigating undesired effects of hysteresis nonlinearity. The reported studies have shown that the hysteresis nonlinearity of magnetostrictive actuators is strongly coupled with various operating factors such as input frequency, magnetic bias and current amplitude (Liu et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

A Modified Prandtl-Ishlinskii Hysteresis Modeling Method with Load-dependent Delay for Characterizing Magnetostrictive Actuated Systems

Feng

Rakheja

et al. 2018

Mech. Sci.

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Abstract. The actuating precision of a micro-positioning system, driven by a magnetostrictive actuator, is adversely limited by its nonlinearities, particularly the output-input hysteresis, which are further affected by the operating load and input frequency. In this paper, the output-input properties of a magnetostrictive actuated system are experimentally characterized considering a wide range of operating frequencies and loads. The measured data revealed that the hysteresis behaviour is strongly affected with a change of operating load, and a modified Prandtl-Ishlinskii model with load-dependent delay is subsequently formulated to describe the nonlinear characteristics of the magnetostrictive actuated system in terms of major and minor loop hysteresis, and output magnitude and phase responses. The proposed model integrates a load-delay function related to the load mass with the Prandtl-Ishlinskii hysteresis model so as to fully describe the coupled nonlinear delay effects of the system output. The validity of the proposed model is demonstrated through comparisons with the experimental data for a range of operating loads and frequencies. It is shown that the proposed model can accurately describe the load-dependent hysteresis effects of the magnetostrictive actuated system up to certain input frequencies.

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“…The robust SAB scheme of (Zhou et al, 2004), (Su et al, 2009), (Feng, Hong, Chen & Su, 2008) has the advantage that the knowledge on the upper or lower bounds of the plant coefficients can be relaxed if the controller is properly designed and the control gain is constant or known. The approach is based on the truncation method of (Slotine & Li, 1991), pp.…”

Section: Introductionmentioning

confidence: 99%