Dynamic Preisach modelling of hysteresis for the piezoceramic actuator system

Yu, Yunhe; Xiao, Zenngchu; Naganathan, Nagi G.; Dukkipati, Rao V.

doi:10.1016/s0094-114x(01)00060-x

Cited by 102 publications

(31 citation statements)

References 8 publications

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“…Therefore, the paper adopted a inverse dynamic Preisach model based on the dynamic Preisach model (18) to solve the control problem of rate-dependent hysteresis nonlinearity of piezoelectric direct drive electro-hydraulic servo valve. By introducing a function of expressing the rate change in the modified Preisach model, the dynamic Preisach model is described as:…”

Section: Dynamic Preisach Model For the Piezoelectric Direct Drive Elmentioning

confidence: 99%

High Precise Fuzzy Control for Piezoelectric Direct Drive Electro-Hydraulic Servo Valve

Zhou

Gao

Yang

et al. 2012

JAMDSM

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As the core part of the electro-hydraulic servo system, the electro-hydraulic servo valve plays an important role in the system. Due to the piezoelectric actuator has characteristics of fast response, easy control and high control accuracy, it can be used as the electric-mechanical converter of the electro-hydraulic servo valve. However, this kind of the piezoelectric direct drive electro-hydraulic servo valve has hysteresis and creep nonlinearities. In order to improve the output accuracy of the system, a high-precise fuzzy control method with the dynamic Preisach model in feedforward loop is proposed. The control scheme is separated into two parts: a feedforward loop with the dynamic Preisach model and a feedback loop with high precise fuzzy control. The high precision fuzzy control adopts Lagrange interpolation method. The experimental results show that the proposed method can resolve the hysteresis and creep nonlinearities and reach a higher dynamic performance, the control effect is better than the conventional fuzzy control method.

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Section: Dynamic Preisach Model For the Piezoelectric Direct Drive Elmentioning

confidence: 99%

High Precise Fuzzy Control for Piezoelectric Direct Drive Electro-Hydraulic Servo Valve

Zhou

Gao

Yang

et al. 2012

JAMDSM

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“…Bertotti [12] proposed a dynamic generalization of the scalar Preisach model by assuming the input rate-dependent behavior of delayed relays. By introducing the dependence of the Preisach function on the input variation rate, Yu et al [13] developed a new dynamic Preisach model. Mrad and Hu [14] presented a dynamic Preisach hysteresis model to describe hysteresis nonlinearity of piezoceramic actuators up to 800 Hz by adopting an average input rate-dependent density function.…”

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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“…It is very difficult to capture the complicated rate-dependent hysteretic behavior precisely. In addition, majority of the existing models employ a large number of parameters to describe the rate-dependent hysteresis [1,21], which may block their applications in high-speed real-time control as an adverse effect.Recently, it has been shown that ANN provides an efficient way to model the nonlinear hysteresis [5,20]. Nevertheless, there is no universal method to determine an optimal ANN structure in terms of the number of hidden layers and number of neurons in each layer.…”

mentioning

confidence: 99%

Feedforward Control Based on Inverse Hysteresis Models

Tan

2015

Advances in Industrial Control

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This chapter presents the rate-dependent hysteresis compensation of a piezoelectric nanopositioning stage using the feedforward control based on an inverse hysteresis model. Three different controllers are realized and compared, which employ Bouc-Wen model, modified Prandtl-Ishlinskii (MPI) model, and least squares support vector machines (LSSVM)-based intelligent model, respectively. Experimental studies demonstrate the superiority of LSSVM model in hysteresis modeling and compensation tasks. IntroductionIn order to compensate for the hysteresis effect, the hysteresis behavior is usually modeled by Preisach model [3,6], Prandtl-Ishlinskii model [7], Bouc-Wen model [11,12], Maxwell-based model [8], Dahl model [18], polynomial model [9], etc. Then, an inverse hysteresis model is constructed and utilized as a feedforward controller to cancel the hysteresis effect. However, the hysteresis effect is dependent not only on the amplitude but also on the frequency of input signals. It is very difficult to capture the complicated rate-dependent hysteretic behavior precisely. In addition, majority of the existing models employ a large number of parameters to describe the rate-dependent hysteresis [1,21], which may block their applications in high-speed real-time control as an adverse effect.Recently, it has been shown that ANN provides an efficient way to model the nonlinear hysteresis [5,20]. Nevertheless, there is no universal method to determine an optimal ANN structure in terms of the number of hidden layers and number of neurons in each layer. Moreover, ANN exhibits the problems of overfitting and sinking into local optima, which are their major drawbacks in practical implementation. Alternatively, SVM gives a promising way to estimate nonlinear system models accurately. Based on the statistical learning theory and structural risk minimization principle, the SVM approach is capable of modeling nonlinear systems by trans-

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Dynamic Preisach modelling of hysteresis for the piezoceramic actuator system

Cited by 102 publications

References 8 publications

High Precise Fuzzy Control for Piezoelectric Direct Drive Electro-Hydraulic Servo Valve

High Precise Fuzzy Control for Piezoelectric Direct Drive Electro-Hydraulic Servo Valve

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

Feedforward Control Based on Inverse Hysteresis Models

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