Inverse Rate-Dependent Prandtl–Ishlinskii Model for Feedforward Compensation of Hysteresis in a Piezomicropositioning Actuator

Janaideh, Mohammad Al; Krejčı́, Pavel

doi:10.1109/tmech.2012.2205265

Cited by 174 publications

(82 citation statements)

References 33 publications

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“…Notice that the LTI approximation of the creep is important within different applications: modeling, feedforward control, feedback control and signal estimation [5][6][7][8][9][10][11][12][13][14][15]. Γ d (u(s), s) is mainly described by a rate-dependent Prandtl-Ishlinskii model [16][17][18][19]. Rate-dependent models are however, more complex to handle than rate-independent hysteresis models.…”

Section: Pea Nonlinear Modelingmentioning

confidence: 99%

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Getting Started with PEAs-Based Flapping-Wing Mechanisms for Micro Aerial Systems

et al. 2016

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This paper introduces recent advances on flapping-wing Micro and Nano Aerial Vehicles (MAVs and NAVs) based on Piezoelectric Actuators (PEA). Therefore, this work provides essential information to address the development of such bio-inspired aerial robots. PEA are commonly used in micro-robotics and precise positioning applications (e.g., micro-positioning and micro-manipulation), whereas within the Unmanned Aerial Vehicles (UAVs) domain, motors are the classical actuators used for rotary or fixed-wing configurations. Therefore, we consider it pertinent to provide essential information regarding the modeling and control of piezoelectric cantilever actuators to accelerate early design and development stages of aerial microrobots based on flapping-wing systems. In addition, the equations describing the aerodynamic behavior of a flapping-wing configuration are presented.

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Section: Pea Nonlinear Modelingmentioning

confidence: 99%

“…Many studies have been carried out regarding voltage control of hysteresis [16][17][18][19][20]24,25,27,28], creep [9], and of underdamped vibrations [35,36] in PEA, or their control simultaneously [10,21]. The main limitation of feed-forward control is the restricted robustness to model uncertainties and external disturbances.…”

Section: Pea Controlmentioning

confidence: 99%

Getting Started with PEAs-Based Flapping-Wing Mechanisms for Micro Aerial Systems

et al. 2016

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“…Figure 7 shows the comparison of the measured hysteresis loops with those predicted from the modified P-I model under the sinusoidal input signals at 10, 400 and 1,200 Hz. The hysteresis loops predicted from the rate-independent P-I model [8] and the rate-dependent P-I model based on dynamic thresholds [19,20] are also plotted in Figure 7 for comparison. The dynamic threshold function used in the rate-dependent P-I model [19,20] is defined as: r i (v(t)) = αi + β |v(t)|, where α and β are constants.…”

Section: Model Verificationmentioning

confidence: 99%

“…The contributions of this work are threefold: 1. Distinct from the works [16][17][18][19][20][21], the modified P-I model proposed for rate-dependent hysteresis in this work is constructed by a rate-independent P-I model in conjunction with a mth-power velocity damping model. 2.…”

Section: Introductionmentioning

confidence: 99%

A Modified Prandtl-Ishlinskii Model for Rate-dependent Hysteresis Nonlinearity Using mth-power Velocity Damping Mechanism

Yang

et al. 2014

International Journal of Advanced Robotic Systems

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Hysteresis of piezoelectric actuators is rate-dependent at high frequencies, but most of the hysteresis models are rate-independent and cannot describe the rate-dependent hysteresis nonlinearity independently. In this paper, a modified Prandtl-Ishlinskii (P-I) model is proposed to characterize the rate-dependent hysteresis of piezoelectric actuators under sinusoidal excitation. This model is formulated by a mth-power velocity damping model in conjunction with the rate-independent P-I model. The parameter identification of this model is divided into two steps using different experimental data and algorithms.The particle swarm optimization is introduced first to identify the rate-independent parameters, and the nonlinear least square method is adopted afterwards to identify the rate-dependent parameters which are functions of the excitation frequency. Moreover, the proposed P-I model is developed to describe hysteresis nonlinearity under triangular excitation by introducing weighted functions, i.e., λ i . Finally, the model results attained under the sinusoidal and triangular inputs at different frequencies are compared with the corresponding experimental data. The comparisons demonstrate that the proposed P-I model can well describe hysteresis nonlinearity under sinusoidal excitation up to 1,500 Hz and triangular excitation up to 250 Hz, respectively.

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“…Based on the similar idea of constructing novel density functions, a modified Preisach model [17] and two generalized PI-type models [18,19] were presented. Besides, Janaideh [20] provided a dynamic PI-type hysteresis model constructed with a time-dependent threshold variable. These dynamic hysteresis models were proved practically possess much better accuracy than the static models to estimate hysteresis nonlinearity for PEAs driven by one dynamic voltage signal.…”

Section: Introductionmentioning

confidence: 99%

Identification and experimental assessment of two-input Preisach model for coupling hysteresis in piezoelectric stack actuators

Dong

Wang

2014

Sensors and Actuators A: Physical

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Inverse Rate-Dependent Prandtl–Ishlinskii Model for Feedforward Compensation of Hysteresis in a Piezomicropositioning Actuator

Cited by 174 publications

References 33 publications

Getting Started with PEAs-Based Flapping-Wing Mechanisms for Micro Aerial Systems

Getting Started with PEAs-Based Flapping-Wing Mechanisms for Micro Aerial Systems

A Modified Prandtl-Ishlinskii Model for Rate-dependent Hysteresis Nonlinearity Using mth-power Velocity Damping Mechanism

Identification and experimental assessment of two-input Preisach model for coupling hysteresis in piezoelectric stack actuators

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