Development of a System Incorporating a Multifunctional Actuator Using an Intelligent Multifunction Control Method

Kazuki Kuribayashi; Seiji Yasunobu

doi:10.20965/jaciii.2012.p0662

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JACIII Vol.16 No.5 pp. 662-667

doi: 10.20965/jaciii.2012.p0662

(2012)

Paper:

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Development of a System Incorporating a Multifunctional Actuator Using an Intelligent Multifunction Control Method

Kazuki Kuribayashi and Seiji Yasunobu

Division of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

Received:

December 28, 2011

Accepted:

April 17, 2012

Published:

July 20, 2012

Keywords:

intelligent multi-input multi-output control (iMIMOc), predictive fuzzy control, multifunctional actuator, multifunction control system

Abstract

Next-generation robots, such as humanoid robots, require a multifunction control system. In the present study, a multifunctional actuator is considered in order to construct a multifunction control system more simply. The multifunctional actuator can easily set the parameters of target angle and stiffness, but determining the appropriate parameters is difficult. Therefore, in order to address this difficulty, we construct an intelligent controller based on iMIMOc. This iMIMOc is applied to a robot that incorporates multifunctional actuators, and an iMIMOc system is developed. The effectiveness of the developed system is verified through simulation and real-machine experiments.

Cite this article as:

Kazuki Kuribayashi and Seiji Yasunobu, “Development of a System Incorporating a Multifunctional Actuator Using an Intelligent Multifunction Control Method,” J. Adv. Comput. Intell. Intell. Inform., Vol.16, No.5, pp. 662-667, 2012.

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References

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[6] S. Yasunobu, A. Miyamoto, and H. Ihara, “Automatic train operation by predictive fuzzy control,” Proc. of Industrial Application of Fuzzy Control, North Holland, pp. 1-18, 1985.
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[1] [1] M. Yamada, S. Sano, and N. Uchiyama, “Landing Control of Foot with Springs for Walking Robots on Rough Terrain,” Proc. of Int. J. of Advanced Robotic Systems, Vol.6, No.3, pp. 201-206, 2009.

[2] [2] S. Murai and Y. Fujimoto. “Control of Spring Actuator and Its Application to Biped Robot,” Proc. of Advanced Motion Control, 9th IEEE Int. Workshop, pp. 411-415, 2006.

[3] [3] L. A. Zadeh, “Fuzzy sets,” Proc. of Information and Control, Vol.8, pp. 338-353, 1965.

[4] [4] L. A. Zadeh, “Outline of a New Approach to the Analysis of Complex Systems and Decision Processes,” Proc. of IEEE Trans. SMC, Vol.3, No.1, pp. 28-44, 1973.

[5] [5] E. H. Mamdani, “Applications of Fuzzy Algorithms for Control of a Simple Dynamic Plant,” Proc. of IEEE, pp. 1585-1588, 1974.

[6] [6] S. Yasunobu, A. Miyamoto, and H. Ihara, “Automatic train operation by predictive fuzzy control,” Proc. of Industrial Application of Fuzzy Control, North Holland, pp. 1-18, 1985.

[7] [7] P. L. Falb and W. A.Wolovich, “Decoupling in the Design and Synthesis of Multivariable Control Systems,” Proc. of IEEE Trans. on Automatic Control, AC-12, pp. 651-659, 1967.

[8] [8] E. G. Gilbert, “The Decoupling of Multivariable Systems by State Feedback,” Proc. of SIAM J. on Control, Vol.7, No.1, pp. 50-64, 1969.

[9] [9] G. Inoue and S. Yasunobu, “An Intelligent MIMO Control and Its Application to Two-wheeled Vehicle for Driving Support,” Proc. of 7th World Congress on Intelligent Control and Automation, pp. 2804-2809, 2008.