History of Robotics Research and Development of Japan2012SensingParabolic Sliding Mode Noise-Reduction Filters for Mechatronic Systems

Shanhai JinKyushu University
Ryo KikuuweKyushu University
Motoji YamamotoKyushu University
In this research, the authors proposed a new sliding mode filter for effectively removing various noise. The filter employs a parabolic-shaped sliding surface, which is designed so that the output converges to the input value in finite-time when a constant input is provided, and thus it is referred to as parabolic sliding mode filter (PSMF). One of major advantages of PSMF is that it produces smaller phase lag than linear filters and a conventional parabolic sliding mode filter. The effectiveness of PSMF was validated through its application to a feedback, force control of a robot manipulator. In addition, the authors presented an Adaptive Windowing PSMF (AW-PSMF), which is an improved version of PSMF, for obtaining smooth and reliable differential signal. In AW-PSMF, the window size is adaptively changed to find a window size that optimizes the trade-off between the output smoothness and the suppression of delay in numerical differentiation. The effectiveness of AW-PSMF in improving velocity feedback for position control was experimentally confirmed. 1th RSJ Advanced Robotics Best Paper Award in 2013.
The parabolic-shaped sliding surface (solid curve) and state trajectories (thin curves) of the proposed filters


Correspondence papers

Shanhai Jin, Ryo Kikuuwe, and Motoji Yamamoto:Realtime Quadratic Sliding Mode Filter for Removing Noise

Advanced Robotics, vol. 26, no. 8-9, pp. 877-896, 2012.

Shanhai Jin, Ryo Kikuuwe, and Motoji Yamamoto:Parameter Selection Guidelines for a Parabolic Sliding Mode Filter Based on Frequency and Time Domain Characteristics

Journal of Control Science and Engineering, vol. 2012, article 923679, 2012. doi:10.1155/2012/923679.

Shanhai Jin, Ryo Kikuuwe, and Motoji Yamamoto:Improving Velocity Feedback for Position Control by Using a Discrete-Time Sliding Mode Filtering with Adaptive Windowing

Advanced Robotics, vol. 28, no.14, pp. 943-953, 2014.

Related papers

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[2] T. Emaru and T. Tsuchiya: "Research on estimating the smoothed value and the differential of the sensor inputs by using sliding mode system (application to ultrasonic wave sensor)," Transactions of the Japan Society of Mechanical Engineers C, vol. 66, no. 652, pp. 3947–3954, 2000. (in Japanese)

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[5] R. Kikuuwe, N. Takesue and H. Fujimoto: "A control framework to generate nonenergy-storing virtual fixtures: use of simulated plasticity," IEEE Transactions on Robotics, vol. 24, no. 4, pp. 781–793, 2008.

[6] R. Kikuuwe, S. Yasukouchi, H. Fujimoto and M. Yamamoto: "Proxy-based sliding mode control: a safer extension of PID position control," IEEE Transactions on Robotics, vol. 26, no. 4, pp. 670–683, 2010.

[7] J. Q. Han and Y. C. Huang: "Frequency characteristic of second-order tracking-differentiator," Mathematics in Practice and Theory, vol. 33, no. 3, pp. 71–74, 2003 (in Chinese).

[8] F. Janabi-Sharifi, V.Hayward and C. S. J. Chen: "Discrete-time adaptive windowing for velocity estimation," IEEE Transactions on Control Systems Technology, vol. 8, no. 6, pp. 1003–1009, 2000.

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