NDLI: A minimax control design for nonlinear systems based on genetic programming: Jung's collective unconscious approach

Content Provider	IEEE Xplore Digital Library
Author	Imae, J. Ohtsuki, N. Kikuchi, Y. Kobayashi, T.
Copyright Year	2003
Description	Author affiliation: Osaka Prefecture Univ., Sakai, Japan (Imae, J.; Ohtsuki, N.; Kikuchi, Y.; Kobayashi, T.)
Abstract	When it comes to the minimax controller design, it would be extremely difficult to obtain such controllers in the nonlinear situations. One of the reasons is that the minimax controller should be robust against any kind of disturbances in the nonlinear situations. We propose a difficulty-free design method of minimax control problems. First, based on the genetic programming and Jung's collective unconscious, This work presents a very simple design technique to solve the minimax control problems, where the minimax controller may be constructed only paying attention to the minimization process. It would be surprising that the maximization process is not needed in the construction of minimax controllers. Then, some simulations are given to demonstrate the usefulness of the proposed design technique with the identification problem, and minimax control problems.
Sponsorship	Air Force Iffice of Sci. Res. Asian Office of Aerospace Res and Development Army Res. Office - Far East CISCO Evoluationary Programming Soc. IEE Inst. of Engineers, Australia IEEE Neural Networks Soc. Univ. of New South Wales
Starting Page	1702
Ending Page	1707
File Size	296911
Page Count	6
File Format	PDF
ISBN	0780378040
DOI	10.1109/CEC.2003.1299878
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-12-08
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Minimax techniques Control design Nonlinear systems Genetic programming Control systems Nonlinear control systems Design methodology Partial differential equations Differential equations Optimal control
Content Type	Text
Resource Type	Article

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