Adaptive modified Prandtl-Ishlinskii model for compensation of hysteretic nonlinearities in magnetic shape memory actuators

Riccardi, Leonardo; Naso, David; Turchiano, Biagio; Janocha, Hartmut

doi:10.1109/iecon.2011.6119288

Cited by 8 publications

(7 citation statements)

References 15 publications

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“…When uncertainties and time-variant hysteresis behavior are relatively large and above all slow, then the adaptive strategies such as [30], [33], and [17] can be applied. Because we, however, deal with rather low and fast (sudden) hysteresis distortions, a correspondingly fast and transient counteraction is required.…”

Section: Observer-based Inverse Approachmentioning

confidence: 99%

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Control of Magnetic Shape Memory Actuators Using Observer-Based Inverse Hysteresis Approach

Ruderman

Bertram

2014

IEEE Trans. Contr. Syst. Technol.

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Magnetic shape memory (MSM) actuators belong to active material technologies with a high energy density and outstanding field-strain relation. Large-scale multivariate fieldstress-strain hysteresis effects, however, antagonize their broad use because of the inherent difficulties with control. In this brief, we describe and compare experimentally several MSM control strategies, including the observer-based inverse hysteresis approach proposed in the previous works and combined here with a linear feedback controller by connecting both in parallel. For a prototypic MSM actuator with return spring, it is shown that the actuator plant can be approximated by an appropriate hysteresis operator and a linear transfer function of residual dynamics. The positioning profiles with a bandwidth 0.1-10 Hz and amplitudes between 0.01 and 0.1 mm have been evaluated by the experiments.Index Terms-Control systems, hysteresis, inversion, magnetic shape memory (MSM), observer, Preisach model, smart actuators.

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Section: Observer-based Inverse Approachmentioning

confidence: 99%

“…Concerning the inverse model-based control techniques, an adaptive modified Prandtl-Ishlinskii [16] model has been applied to compensate the hysteresis effects in MSM actuators [17]. Here, a most common actuator structure with the return spring prestressed for MSM counteraction has been considered.…”

Section: Introductionmentioning

confidence: 99%

Control of Magnetic Shape Memory Actuators Using Observer-Based Inverse Hysteresis Approach

Ruderman

Bertram

2014

IEEE Trans. Contr. Syst. Technol.

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“…PI model has a simple structure and does not need large amount of calculation. Riccardi [5] developed a modified PI hysteresis model and utilized its inverse model to compensate the hysteretic characteristic of the MSMA actuator. Duhem model [20À22] is described by the differential equations, and the output is only affected by the increase or decrease of the input.…”

Section: Introductionmentioning

confidence: 99%

“…Webb [16] established an adaptive hysteresis model of the SMA actuator, and realized the adaptive identification and compensation for the SMA actuator by it. PrandtlÀIshlinskii (PI) model [5,18,19] is that the model of the hysteresis characteristic is acquired by an integral of play or stop operators. PI model has a simple structure and does not need large amount of calculation.…”

Section: Introductionmentioning

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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“…Preisach-type hysteresis models, such as Preisach model [9–11], Prandtl-Ishlinskii (PI) model [12, 13], and KP model [14, 15] are the most popular ones which have been widely used in modern control techniques to mitigate the effects of unknown hysteresis. In this paper, a Preisach-type hysteresis model—modified KP model is used to describe the hysteresis of MSMA actuator.…”

Section: Introductionmentioning

confidence: 99%

Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel′skii‐Pokrovskii Model

Zhou

Wang²,

Gao³

2013

The Scientific World Journal

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As a new type of intelligent material, magnetically shape memory alloy (MSMA) has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP) model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.

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Adaptive modified Prandtl-Ishlinskii model for compensation of hysteretic nonlinearities in magnetic shape memory actuators

Cited by 8 publications

References 15 publications

Control of Magnetic Shape Memory Actuators Using Observer-Based Inverse Hysteresis Approach

Control of Magnetic Shape Memory Actuators Using Observer-Based Inverse Hysteresis Approach

Modified KP Model for Hysteresis of Magnetic Shape Memory Alloy Actuator

Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel′skii‐Pokrovskii Model

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