Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel'skii-Pokrovskii Model

Zhou, Miaolei; Wang, Shoubin; Gao, Wei

doi:10.1155/2013/865176

Cited by 10 publications

(7 citation statements)

References 15 publications

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“…For practical application of the actuator, the hysteresis loop curve of the actuator input-output relationship includes a major loop and a minor loop, and in this paper we establish a hysteresis non-linear model based on the KP model to provide an accurate description of the hysteresis loops in the MSMA actuator. The elementary hysteresis operator selected here is the KP operator ( Figure 1 ) [26] , [27] . To implement the KP model in a computer system, the corresponding Preisach plane is discretized.…”

Section: Methodsmentioning

confidence: 99%

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Feedforward-Feedback Hybrid Control for Magnetic Shape Memory Alloy Actuators Based on the Krasnosel'skii-Pokrovskii Model

2014

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As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

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Section: Methodsmentioning

confidence: 99%

“…To obtain the appropriate density parameter, this paper employs the variable step-size recursive least-squares method, which reduces the amount of calculations by merging some repetitive operations in the traditional recursive least-squares algorithm [27] , [28] .…”

Section: Methodsmentioning

confidence: 99%

Feedforward-Feedback Hybrid Control for Magnetic Shape Memory Alloy Actuators Based on the Krasnosel'skii-Pokrovskii Model

2014

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“…The proposed modified KP model [28] has a unidirectional output and it can be described with the Preisach representation as…”

Section: Modified Kp Model Of Msma Actuatormentioning

confidence: 99%

Modified KP Model for Hysteresis of Magnetic Shape Memory Alloy Actuator

Zhou

et al. 2014

IETE Technical Review

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The hysteresis characteristic can significantly decrease the control accuracy of magnetic shape memory alloy actuator. To describe the hysteresis between input signal and the output signal of the magnetic shape memory alloy actuator, a modelling method based on the modified Krasnosel'skiiÀPokrovskii kernel is developed in this paper. The density parameters of the adopted hysteresis model are identified by the recursive least square method. The simulation results reveal that the proposed method has a good performance in describing the hysteresis modelling of magnetic shape memory alloy actuator and the modelling accuracy can be further improved by adjusting the number of Krasnosel'skiiÀPokrovskii kernel. The result showed that the adopted modelling method can accurately describe the hysteresis characteristic of the magnetic shape memory alloy actuator, and the maximum modelling error can be reduced to 0.0022 mm when the number of discretization lines is selected as L D 15.

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“…In the developed model, by considering hyperbolic tangent function as an envelope function, the ability of the model to characterize asymmetric and wide saturation of the MSMA actuator has been improved. Although some rate-independent hysteresis models, such as Krasnoseleski-Pokrovskii 25 and PI 11 models, have been proposed in the literature to describe hysteresis nonlinearities of MSMA actuators, due to the structure of these models, they can only describe the behavior of MSMA actuators at a fixed frequency.…”

Section: Introductionmentioning

confidence: 99%

Experimental characterization and control of a magnetic shape memory alloy actuator using the modified generalized rate-dependent Prandtl–Ishlinskii hysteresis model

Shakiba

Zakerzadeh

Ayati

2018

Proceedings of the Institution of Mechanical Engineers, Part I:

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In this article, two models are used, namely rate-independent and rate-dependent generalized Prandtl-Ishlinskii, to characterize a magnetic shape memory alloy actuator. The results show that the rate-independent model cannot consider the effect of input excitation frequency, while the rate-dependent model omits this drawback by defining a time-dependent operator. For the first time, the effects of excitation frequency on the hysteretic behavior of magnetic shape memory alloy actuator are investigated. In this study, five excitation voltages with different frequencies in the range of 0.05-0.4 Hz are utilized as inputs to the magnetic shape memory alloy actuator and the displacement outputs are measured. Experimental results indicate that, with increasing the excitation frequency, the size of the hysteresis loops changes. Since the generalized rate-dependent Prandtl-Ishlinskii model cannot consider the asymmetric hysteresis loops, in the developed model, a tangent hyperbolic function is applied as an envelope function in order to improve the capability of the model in characterizing the asymmetric behavior of magnetic shape memory alloy actuator. The parameters of both rate-dependent and rate-independent models are identified by genetic algorithm optimization. The results reveal that the rate-independent form is not capable of accurately describing the hysteretic behavior of magnetic shape memory alloy actuator for different input frequencies. Simulation and experimental results also demonstrate the proficiency of the developed model for precise characterization of the saturated rate-dependent hysteresis loops of magnetic shape memory alloy actuator. In addition, the proposed model is utilized for determining a proper range for controller coefficients during controller design.

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Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel'skii-Pokrovskii Model

Cited by 10 publications

References 15 publications

Feedforward-Feedback Hybrid Control for Magnetic Shape Memory Alloy Actuators Based on the Krasnosel'skii-Pokrovskii Model

Feedforward-Feedback Hybrid Control for Magnetic Shape Memory Alloy Actuators Based on the Krasnosel'skii-Pokrovskii Model

Modified KP Model for Hysteresis of Magnetic Shape Memory Alloy Actuator

Experimental characterization and control of a magnetic shape memory alloy actuator using the modified generalized rate-dependent Prandtl–Ishlinskii hysteresis model

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