Modeling and compensation of asymmetric rate-dependent hysteresis of a miniature pneumatic artificial muscle-based catheter

Shakiba, Saeid; Ourak, Mouloud; Poorten, Emmanuel Vander; Ayati, Moosa; Yousefi‐Koma, Aghil

doi:10.1016/j.ymssp.2020.107532

Cited by 42 publications

(22 citation statements)

References 44 publications

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“…Input frequencies up to 1 Hz are investigated in this work. Hysteresis behavior depends on both the input frequency and the amplitude of the excitation signal [25], different excitation frequencies are included in the training data, namely the frequencies of the excitation signal are set to 0.2, 0.4, 0.6 and 0.8 in the training data set. The time constant τ was chosen with only one value τ = 0.15 to generate multi-loop hysteresis.…”

Section: Training Data Acquisitionmentioning

confidence: 99%

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Hysteresis Modeling of Robotic Catheters Based on Long Short-Term Memory Network for Improved Environment Reconstruction

Zhang

Ourak

et al. 2021

IEEE Robot. Autom. Lett.

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Catheters are increasingly being used to tackle problems in the cardiovascular system. However, positioning precision of the catheter tip is negatively affected by hysteresis. To ensure tissue damage due to imprecise positioning is avoided, hysteresis is to be understood and compensated for. This work investigates the feasibility to model hysteresis with a Long Short-Term Memory (LSTM) network. A bench-top setup containing a catheter distal segment was developed for model evaluation. The LSTM was first tested using four groups of test datasets containing diverse patterns. To compare with the LSTM, a Deadband Rate-Dependent Prandtl-Ishlinskii (DRDPI) model and a Support Vector Regression (SVR) model were established. The results demonstrated that the LSTM is capable of predicting the tip bending angle with sub-degree precision. The LSTM outperformed the DRDPI model and the SVR model by 60.1% and 36.0%, respectively, in arbitrarily varying signals. Next, the LSTM was further validated in a 3D reconstruction experiment using Forward-Looking Optical Coherence Tomography (FL-OCT). The results revealed that the LSTM was able to accurately reconstruct the environment with a reconstruction error below 0.25 mm. Overall, the proposed LSTM enabled precise free-space control of a robotic catheter in the presence of severe hysteresis. The LSTM predicted the catheter tip response precisely based on proximal input pressure, minimizing the need to install sensors at the catheter tip for localization.

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Section: Training Data Acquisitionmentioning

confidence: 99%

“…A state-of-the-art analytic model called Deadband Rate-Dependent Prandtl-Ishlinskii (DRDPI) model proposed in [25] was established for comparison to the LSTM. The DRDPI model is a sophisticated and practical model that takes into account the impact of frequency on the pattern of the hysteresis.…”

Section: A Preliminary Evaluation Of the Lstmmentioning

confidence: 99%

Hysteresis Modeling of Robotic Catheters Based on Long Short-Term Memory Network for Improved Environment Reconstruction

Zhang

Ourak

et al. 2021

IEEE Robot. Autom. Lett.

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“…Additionally, the controller cannot cope with environmental perturbations (i.e., temperature changes or external disturbances). For inverse model feedback control, the hysteresis nonlinearity is compensated for by the inverse model compensator, and the feedback loop is then used for ensuring the stability of the system in the presence of disturbances [37][38][39][40]. In [41], an inverse Preisach model was used as a feedforward compensation controller.…”

Section: Symbols B Smentioning

confidence: 99%

“…Theorem 1: Consider the entire control system, which is composed of the piezoelectric positioning stage system (14), the updated laws (37,38), the actual controller (34), and the Lyapunov function (39). If Assumptions 1-3 are satisfied, all the signals in the closed-loop systems are uniformly ultimately bounded, and the tracking error e 1 exhibits asymptotic convergence under properly selected design parameters k 1 , k 2 , λ , γ, and η. Additionally, the output displacement x(t) can accurately track the reference displacement signal x d (t) for all t ≥ 0.…”

Section: Robust Adaptive Controller Designmentioning

confidence: 99%

Rate-dependent Asymmetric Hysteresis Modeling and Robust Adaptive Trajectory Tracking for Piezoelectric Micropositioning Stages

Nie

Luo

Gao

et al. 2021

Preprint

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Hysteresis is an inherent characteristic of piezoelectric materials that can be determined by not only the historical input but also the input signal frequency. Hysteresis severely degrades the positioning precision of piezoelectric micropositioning stages. In this study, the hysteresis characteristics and the excitation frequency effects on the hysteresis behaviors of the piezoelectric micropositioning stage are investigated. Accordingly, a rate-dependent asymmetric hysteresis Prandtl-Ishlinskii (RDAPI) model is developed by introducing a dynamic envelope function into the play operators of the Prandtl-Ishlinskii (PI) model. The RDAPI model uses a relatively simple analytical structure with fewer parameters then other modified PI model to characterize the rate-dependent and asymmetric hysteresis behavior in piezoelectric micropositioning stages. Considering practical situations with the uncertainties and external disturbances associated with the piezoelectric micropositioning stages, the system dynamics are described using a second-order differential equation. On this basis, a corresponding adaptive robust control method that does not involve the construction of a complex hysteretic inverse model is developed. The Lyapunov analysis method proves the stability of the entire closed-loop control system. Experiments confirm that the proposed RDAPI model achieves a significantly improved accuracy compared with the PI model. Furthermore, compared with the inverse RDAPI model-based feedforward compensation and the inverse RDAPI model-based proportional-integral-derivative control methods, the proposed robust adaptive control strategy exhibits improved tracking performance.

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Section: Introductionmentioning

confidence: 99%

Rate-dependent asymmetric hysteresis modeling and robust adaptive trajectory tracking for piezoelectric micropositioning stages

et al. 2022

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Hysteresis is an inherent characteristic of piezoelectric materials that can be determined by not only the historical input but also the input signal frequency. Hysteresis severely degrades the positioning precision of piezoelectric micropositioning stages. In this study, the hysteresis characteristics and the excitation frequency effects on the hysteresis behaviors of the piezoelectric micropositioning stage are investigated. Accordingly, a rate-dependent asymmetric hysteresis Prandtl-Ishlinskii (RDAPI) model is developed by introducing a dynamic envelope function into the play operators of the Prandtl-Ishlinskii (PI) model. The RDAPI model uses a relatively simple analytical structure with fewer parameters then other modified PI model to characterize the rate-dependent and asymmetric hysteresis behavior in piezoelectric micropositioning stages. Considering practical situations with the uncertainties and external disturbances associated with the piezoelectric micropositioning stages, the system dynamics are described using a secondorder differential equation. On this basis, a corresponding adaptive robust control method that does not involve the construction of a complex hysteretic inverse model is developed. The Lyapunov analysis method proves the stability of the entire closed-loop control system. Experiments confirm that the proposed RDAPI model achieves a significantly improved accuracy compared with the PI model. Fur-

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Modeling and compensation of asymmetric rate-dependent hysteresis of a miniature pneumatic artificial muscle-based catheter

Cited by 42 publications

References 44 publications

Hysteresis Modeling of Robotic Catheters Based on Long Short-Term Memory Network for Improved Environment Reconstruction

Hysteresis Modeling of Robotic Catheters Based on Long Short-Term Memory Network for Improved Environment Reconstruction

Rate-dependent Asymmetric Hysteresis Modeling and Robust Adaptive Trajectory Tracking for Piezoelectric Micropositioning Stages

Rate-dependent asymmetric hysteresis modeling and robust adaptive trajectory tracking for piezoelectric micropositioning stages

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