Control of nonlinear mechatronics systems by using universal learning networks

Chun zhi Jin, Kotaro Hirasawa, Murata Junichi, Takayuki Furuzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Nonlinear elements such as friction, dead zone, backlash are mixed in most mechatronics systems, and these are factors that make control accuracy of systems decrease and cause an oscillation. It is difficult to deal with the problems of modeling and control of such systems using common sigmoidal neural networks because there exist nonsmooth nonlinearities in the systems, and there is no easy way to incorporate knowledge and experiences accumulated from past study. In this paper, a design method for nonlinear mechatronics control systems is proposed, in which both of the control object and its controller are represented by using a Universal Learning Network, and the network parameters are trained using a random search algorithm called RasID. In this approach, knowledge and experience about models and controllers are easily incorporated into the network including the nonlinear elements and their compensation elements expressed by non-differentiable functions. Some simulations of a nonlinear crane control system with dead-zone characteristic were carried out. The effectiveness of the proposed design method is illustrated via simulations.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Systems, Man and Cybernetics
PublisherIEEE
Volume5
Publication statusPublished - 1999
Externally publishedYes
Event1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn
Duration: 1999 Oct 121999 Oct 15

Other

Other1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics'
CityTokyo, Jpn
Period99/10/1299/10/15

Fingerprint

Mechatronics
Control systems
Controllers
Cranes
Friction
Neural networks

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Systems Engineering

Cite this

Jin, C. Z., Hirasawa, K., Junichi, M., & Furuzuki, T. (1999). Control of nonlinear mechatronics systems by using universal learning networks. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (Vol. 5). IEEE.

Control of nonlinear mechatronics systems by using universal learning networks. / Jin, Chun zhi; Hirasawa, Kotaro; Junichi, Murata; Furuzuki, Takayuki.

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. Vol. 5 IEEE, 1999.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jin, CZ, Hirasawa, K, Junichi, M & Furuzuki, T 1999, Control of nonlinear mechatronics systems by using universal learning networks. in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. vol. 5, IEEE, 1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics', Tokyo, Jpn, 99/10/12.
Jin CZ, Hirasawa K, Junichi M, Furuzuki T. Control of nonlinear mechatronics systems by using universal learning networks. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. Vol. 5. IEEE. 1999
Jin, Chun zhi ; Hirasawa, Kotaro ; Junichi, Murata ; Furuzuki, Takayuki. / Control of nonlinear mechatronics systems by using universal learning networks. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. Vol. 5 IEEE, 1999.
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