Paper:
Statistical Characteristics of Biomimetic Image-Based Inverted Pendulum Control Systems Using Just-In-Time Method
Shun Ushida*, Ken-ichiro Fukuda**, and Koichiro Deguchi***
*Department of Mechanical Engineering, Osaka Institute of Technology, 5-16-1 Omiya, Asahi, Osaka 535-8585, Japan
**Sony Corporation, 1-7-1 Konan, Minato, Tokyo, Japan
***Tohoku University, 6-6-01 Aramaki-Aza-Aoba, Aoba, Sendai, Japan
We analyzed the behavior of such mechanical systems statistically to determine the on-off intermittency and the power law in the human stick-balancing task. Statistically analyzing pendulum behavior may enable us to interpret human motor control.
- [1] J. L. Cabrera and J. G. Milton, “On-Off Intermittency in a Human Balancing Task,” Physical Review Letters, Vol.89, 158702, 2002.
- [2] J. L. Cabrera and J. G. Milton, “Stick Balancing, On-Off Intermittency, and Survival Times,” Nonlinear Studies, Vol.11, No.3, pp. 305-317, 2004.
- [3] J. L. Cabrera and J. G. Milton, “Human Stick Balancing, Tuning Lèvy Flights to Improve Balance Control,” Chaos, Vol.14, No.3, pp. 691-698, 2004.
- [4] J. L. Cabrera, T. Ohira, and J. G. Milton, “State-Dependent Noise, and Human Balancing Control,” Fluctuation and Noise Letters, Vol.4, pp. L107-L117, 2004
- [5] R. Weron, “Levy-stable distributions revisited, Tail index>2 does not exclude the Levy-stable regime,” Int. Journal ofModern Physics C, Vol.12, No.2, pp. 209-223, 2001.
- [6] J. Heagy, N. Platt, and S. Hammel, “Characterization of On-off Intermittency,” Physical Review E, Vol.49, No.2, pp. 1140-1150, 1994.
- [7] J. Lee, S. Ushida, K. Fukuda, and K. Deguchi, “Stabilization of Inverted Pendulum System based on Sensor Signal with Time Delay,” 226th SICE Tohoku Division Simposium, pp. 226-227, 2005 (in Japanese).
- [8] K. Fukuda, S. Ushida, and K. Deguchi, “Just-In-Time Control of Image-Based Inverted Pendulum Systems with Time-Delay as a Human Motor Control Simulator,” Vol.20, No.4, pp. 167-173, 2007 (in Japanese).
- [9] Q. Zheng and H. Kimura, “Just-In-TimeModeling for Function Prediction and its Applications,” Asian J. Control. Vol.3, No.1, pp. 35-44, 2001.
- [10] C. G. Atkeson, A. W. Moore, and S. Schall, “Locally Weighted Learning,” Artificial Intelligence Review, Vol.11, pp. 11-73, 1997.
- [11] S. Ushida and H. Kimura, “Just-In-Time Approach to Nonlinear Identification and Control,” Journal of the Society of Instrument and Control Engineers, Vol.44, No.2, 2005 (in Japanese).
- [12] M. Ito, S. Matsuzaki, H. Ogai, N. Odate, K. Uchida, S. Saito, and N. Sasaki, “Large Scale Database-based Online Modeling on Blast Furnace Operation,” Tetsu-to-Hagané, Vol.90, No.11, 2004 (in Japanese).
- [13] H. Shigemori, N. Hirata, N. Ikeda, and N. Mizushima, “Rolling set-up modeling for a steel plate by using just-in-time method,” Int. Conf. on Instrumentation, Control and Information Technology (SICE2005), MP 2-9-1, 2005.
- [14] D. W. Aha, “Lazy Learning,” Boston, London, Kluwer Academic Publishers, 1997.
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