Enhancement of cutting force observer by identification of position and force-amplitude dependent model parameters

Shuntaro Yamato, Akihiro Sugiyama, Norikazu Suzuki, Naruhiro Irino, Yasuhiro Imabeppu, Yasuhiro Kakinuma

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


External sensor-less cutting force estimation has good potential in terms of its sustainability. However, its accuracy will deteriorate due to variation of machine dynamics depending on the stage position and cutting force amplitude. In the conventional methods, the physical model parameters such as the axial stiffness and viscous damping coefficient are regarded as constant values identified at a certain condition. As a result, the estimation accuracy decreases because the above parameter variation is not considered. To tackle this issue, a simple parameter identification method in time domain by employing the least-squares method (LSM) and a cutting force estimation by a load-side disturbance observer (LDOB) are proposed for a full-closed controlled ball-screw-driven stage. A series of excitation tests were conducted at different stage positions and various excitation amplitudes in order to capture the position and force-amplitude dependent model parameters. The difference of model behavior in the moving and stopped condition of the stage was also investigated. The position and force-amplitude dependent model parameters captured by the proposed method are installed into the observer. The validity of the proposed method was evaluated through end-milling tests. The experimental results clearly showed that the estimation accuracy of cutting force can be greatly improved in both feed and cross-feed directions by taking into account the position and force-amplitude dependency of physical model parameters.

Original languageEnglish
Pages (from-to)3589-3605
Number of pages17
JournalInternational Journal of Advanced Manufacturing Technology
Issue number9-12
Publication statusPublished - 2019 Oct 1


  • Ball-screw-driven stage
  • Disturbance observer
  • Parameter identification
  • Process monitoring
  • Sensor-less

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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