Adaptive Vibration Suppression in High-Speed Precision Drives Using Multi-Modal Sensor Fusion and Actuator Parameter Tuning

ArticleAçık Erişim

Özet

Background High-speed precision drive systems, such as servo motors and fast-steering platforms, are often affected by coupled torsional and bending vibrations. These vibrations reduce system stability, prolong settling time, and limit achievable control bandwidth, particularly in applications requiring high precision and rapid response. Purpose This study aims to develop a simulation-based adaptive vibration suppression approach capable of simultaneously mitigating torsional and bending vibrations while enhancing dynamic performance and control accuracy in high-speed precision drive systems. Methods A simulation model of a high-speed precision drive system was developed by integrating a distributed multi-modal sensor network with an adaptive control strategy. The system incorporates fiber Bragg grating (FBG) strain sensors, piezoelectric torque sensors, and MEMS accelerometers to monitor vibration modes. A real-time sensor-fusion algorithm identifies dominant vibration frequencies and modes, and an adaptive PD controller dynamically adjusts actuator parameters-such as torque limits, damping coefficients, and phase compensation-based on the simulated structural response under different disturbance scenarios. Results Simulation results clearly demonstrate the effectiveness of the proposed method. Time-domain analysis shows that peak torsional vibration amplitudes are reduced by 65%, while bending vibration amplitudes are reduced by 58%. RMS analysis indicates that torsional vibrations decrease from 0.021 rad to 0.008 rad, and bending vibrations decrease from 0.018 m to 0.007 m. In addition, the adaptive control strategy improves settling time by 40% and provides a more stable steady-state response compared to conventional fixed-gain controllers. Conclusions The results confirm that the proposed simulation-based adaptive vibration suppression system effectively reduces multi-mode vibrations and enhances system stability. By combining distributed sensing, real-time modal analysis, and adaptive actuator tuning within a simulation framework, the approach provides a robust and efficient solution, demonstrating strong potential for the development of self-sensing and self-tuning high-speed precision drive systems.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/ebyu/16419Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1007/s42417-026-02439-2Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorCan, Erol
dc.date.accessioned2026-10-18T20:34:03.088692744Z
dc.date.available2026-10-18T20:34:03.088692744Z
dc.date.issued2026
dc.description.abstractBackground High-speed precision drive systems, such as servo motors and fast-steering platforms, are often affected by coupled torsional and bending vibrations. These vibrations reduce system stability, prolong settling time, and limit achievable control bandwidth, particularly in applications requiring high precision and rapid response. Purpose This study aims to develop a simulation-based adaptive vibration suppression approach capable of simultaneously mitigating torsional and bending vibrations while enhancing dynamic performance and control accuracy in high-speed precision drive systems. Methods A simulation model of a high-speed precision drive system was developed by integrating a distributed multi-modal sensor network with an adaptive control strategy. The system incorporates fiber Bragg grating (FBG) strain sensors, piezoelectric torque sensors, and MEMS accelerometers to monitor vibration modes. A real-time sensor-fusion algorithm identifies dominant vibration frequencies and modes, and an adaptive PD controller dynamically adjusts actuator parameters-such as torque limits, damping coefficients, and phase compensation-based on the simulated structural response under different disturbance scenarios. Results Simulation results clearly demonstrate the effectiveness of the proposed method. Time-domain analysis shows that peak torsional vibration amplitudes are reduced by 65%, while bending vibration amplitudes are reduced by 58%. RMS analysis indicates that torsional vibrations decrease from 0.021 rad to 0.008 rad, and bending vibrations decrease from 0.018 m to 0.007 m. In addition, the adaptive control strategy improves settling time by 40% and provides a more stable steady-state response compared to conventional fixed-gain controllers. Conclusions The results confirm that the proposed simulation-based adaptive vibration suppression system effectively reduces multi-mode vibrations and enhances system stability. By combining distributed sensing, real-time modal analysis, and adaptive actuator tuning within a simulation framework, the approach provides a robust and efficient solution, demonstrating strong potential for the development of self-sensing and self-tuning high-speed precision drive systems.
dc.description.sponsorshipOpen access funding provided by the Scientific and Technological Research Council of Turkiye (TUB & Idot;TAK).
dc.identifier.doi10.1007/s42417-026-02439-2
dc.identifier.eissn2523-3939
dc.identifier.issn2523-3920
dc.identifier.issue4
dc.identifier.startpage208
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/16419
dc.identifier.volume14
dc.identifier.wosWOS:001729844800002
dc.language.isoen
dc.publisherSPRINGER HEIDELBERG
dc.relation.ispartofJOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectHigh-speed precision drives
dc.subjectAdaptive vibration control
dc.subjectMulti-modal sensors
dc.subjectFiber Bragg grating
dc.subjectReal-time actuator tuning
dc.subjectTorsion and bending vibrations
dc.subjectSensor fusion
dc.subjectEngineering, Mechanical
dc.subjectMechanics
dc.subjectEngineering
dc.titleAdaptive Vibration Suppression in High-Speed Precision Drives Using Multi-Modal Sensor Fusion and Actuator Parameter Tuning
dc.typeArticle
dspace.entity.typePublication
rdl.citation.wos2
rdl.oa.statusopen
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)