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Variable structure systems theory in computational intelligence

chapter
posted on 06.12.2017, 00:00 by M Efe, O Kaynak, Xinghuo Yu
Intelligence in the form of well-organized solutions to the ill-posed problems has been the primary focus of many engineering applications. The eve-rincreasing developments in data fusion, sensor technology and high-speed microprocessors made the design in digital domain with high performance. A natural consequence of the progression during the last few decades is the emergence of computationally intelligent systems. Neural networks and fuzzy inference systems constitute the core approaches of computational intelligence, whose methods have extensively been used in the applications extending from image/pattern recognition to identification and control of nonlinear systems. This chapter is devoted to the analysis and design of learning strategies in the context of variable structure systems. Several approaches are discussed in detail with special emphasis on the sliding mode control of nonlinear systems.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Editor

Yu X; Xu J

Start Page

365

End Page

390

Number of Pages

26

ISBN-13

9783540429654

Publisher

Springer

Place of Publication

Berlin, Germany

Open Access

No

Era Eligible

No

Number of Chapters

16

Exports

CQUniversity

Categories

Exports