Modeling and dynamic response of variable mass system of maglev turning electric spindle

Cao, Zheng; Kang, Huimin; Liu, Houcai; Duan, Lianghui; Ouyang, Zhihai; Zhou, Yue; Guan, Jun; Li, Wang

doi:10.1007/s11071-022-07868-8

Cited by 6 publications

(7 citation statements)

References 30 publications

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“…This section completes the simulation in the Simulink environment and gives the simulation results. Related parameters of the RAW system model are shown in Tables 1-5 in the literature (Cao et al, 2022). The initial state variable values are all zero.…”

Section: Simulation Analysismentioning

confidence: 99%

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Adaptive backstepping dynamic sliding mode control for maglev turning motor spindle based on limited time preset performance

Liu

Cao

Kang

et al. 2023

Journal of Vibration and Control

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In the process of turning a maglev motorized spindle, there are problems such as system model time-varying, cross-coupling of control parameters, difficult measurement of system state variables, and nonlinear characteristics of active magnetic bearings, which lead to the inevitable cutting chatter phenomenon, difficult control algorithm design, and then the reduction of workpiece surface quality and accuracy, affecting machining efficiency and tool life. In this paper, the “multimodal-distributed parameter” model is extended to the “magnetic bearing-rotor-workpiece” variable mass turning process. An adaptive backstepping fast dynamic terminal sliding mode control is designed to address the model’s time-varying parameters and cross-coupling issues. In view of the difficulty in measuring the vibration displacement at the cutting point, the displacement field reconstruction method was introduced to reconstruct the vibration displacement field online and provide effective feedback for the previously designed control strategy. Finally, the proposed controller is applied to adjust and control the turning process of a maglev motorized spindle and compared with other advanced controllers. The simulation results show that the proposed control method has a better control effect than other control methods in the presence of unmodeled dynamics, uncertainties, and external disturbances.

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Section: Simulation Analysismentioning

confidence: 99%

“…The differential equation expression of the time function is given (Cao et al, 2022)In the formula,And boldAbold0,boldAbold1,boldAbold2,boldAbold3,boldBbold0,boldBbold1,boldBbold2,boldBbold3,boldBbold4,boldCbold0,boldCbold1, boldCbold2,boldCbold3,boldKbold1,boldKbold2,boldKbold3 are all full arrays that change with time.…”

Section: System Specificationmentioning

confidence: 99%

Adaptive backstepping dynamic sliding mode control for maglev turning motor spindle based on limited time preset performance

Liu

Cao

Kang

et al. 2023

Journal of Vibration and Control

Self Cite

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“…In the realm of system modeling, there exist numerous flexible and powerful nonlinear time series models, such as the exponential autoregressive model [22,9,6], the state-dependent autoregressive model [36,49], and the basis function matrix-based flexible coefficient autoregressive model [8], which consist of a linear blend of exponential or logistic transition functions. These flexible models can capture nonlinear vibration behaviour contained in time series [22,19,11], and have been widely used in modeling the nitrogen oxide (NO x ) decomposition process [35], the magnetic levitation system [37,5], and other applications. In machine learning, several neural networks [47,29,16] can be represented as a linear combination of nonlinear activation functions.…”

Section: Introductionmentioning

confidence: 99%

Multi-innovation-based online variable projection algorithm for a class of nonlinear models

Su,

Chen

et al. 2024

Nonlinear Dyn

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Separable nonlinear models (SNMs) are powerful tools for system identification, data analysis, and machine learning, thanks to their flexible structure and remarkable ability to capture nonlinear behaviors. However, compared with the offline one, the online identification of SNMs is more challenging, due to the dynamic nature of the nonlinear systems and the interdependence of the different parts of parameters in SNMs. Existing methods, such as the recursive Gauss-Newton (RGN) and recursive variable projection (RVP) methods, which cannot effectively handle the parameter interdependence, often suffer from slow convergence and poor performance in this scenario. In this paper, we propose a novel multi-innovation-based recursive variable projection (MIRVP) algorithm, which extends the RVP algorithm with a multi-innovation strategy. This strategy enables the algorithm to handle the interaction of the linear and nonlinear parameters more effectively, by using multiple past innovations instead of only the current one, thus improving the identification effect. We demonstrate the effectiveness of our MIRVP algorithm on both synthetic and real world datasets, showing its advantages in convergence speed and robustness over existing methods.

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“…The variable mass-tuned vibration absorber (VMTVA) which possesses natural frequency that can be adjusted by changing its mass has been implemented as a generalized control strategy to reduce the resonance of a primary system [52]. In addition, it was recently shown that minute variation of mass can significantly impact on the bifurcation voltage of coupled vibrating piezoelectric L-shaped resonator, thereby enabling the detection of micro-mass [53]. In addition, research on PDM has enriched the understanding of a wide range of physical and optical properties of solid materials, such as semiconductors [54], crystalline and helium structures [55] quantum fluids [56], quantum wells and quantum dots [57], to mention but a few.…”

Section: Introductionmentioning

confidence: 99%

Vibrational resonance in a multistable system with position-dependent mass

Roy-Layinde,

Omoteso,

Kolebaje

et al. 2023

Commun. Theor. Phys.

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The occurrence of vibrational resonance (VR) in a dual-frequency-driven multistable system with a spatially varying mass modelling particle with position-dependent mass (PDM) and evolving in a one-dimensional symmetric periodic potential has been investigated and reported in this paper. We numerically computed and analyzed the response amplitude, the effects of the PDM parameters ($m_0,a$) on the potential structure, the occurrence of VR and the bifurcation of the equilibrium points. It is shown that the PDM parameters, besides controlling VR, can induce unconventional resonance patterns through the variation of the potential well depth. The resonant states can be influenced through the cooperation of the PDM parameters and the external forcing leading the system from multiresonance state into single and double resonance states. The contributions of the fixed rest mass $m_0$ on the VR and the PDM-induced resonance are determined by threshold conditions imposed by the magnitude of the mass nonlinear strength $a$.

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Modeling and dynamic response of variable mass system of maglev turning electric spindle

Cited by 6 publications

References 30 publications

Adaptive backstepping dynamic sliding mode control for maglev turning motor spindle based on limited time preset performance

Adaptive backstepping dynamic sliding mode control for maglev turning motor spindle based on limited time preset performance

Multi-innovation-based online variable projection algorithm for a class of nonlinear models

Vibrational resonance in a multistable system with position-dependent mass

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