LEADER 04038nam 22008295 450 001 9910293143503321 005 20250628110028.0 010 $a9783319917078 010 $a3319917072 024 7 $a10.1007/978-3-319-91707-8 035 $a(CKB)4100000004243994 035 $a(DE-He213)978-3-319-91707-8 035 $a(MiAaPQ)EBC5435237 035 $a(Au-PeEL)EBL5435237 035 $a(OCoLC)1040617357 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/44033 035 $a(PPN)22740422X 035 $a(ScCtBLL)cd2a1c9c-45df-4f87-8952-902555e5b6c4 035 $a(Perlego)2338337 035 $a(ODN)ODN0010067679 035 $a(oapen)doab44033 035 $a(oapen)doab30580 035 $a(EXLCZ)994100000004243994 100 $a20180529d2018 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aControl Theory Tutorial $eBasic Concepts Illustrated by Software Examples /$fby Steven A. Frank 205 $a1st ed. 2018. 210 $d2018 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XI, 111 p. 32 illus., 22 illus. in color.) 225 1 $aSpringerBriefs in Applied Sciences and Technology,$x2191-5318 311 08$a9783319917061 311 08$a3319917064 327 $aIntroduction -- Part I: Basic Principles -- Part II: Design Tradeoffs -- Part III: Common Challenges. 330 $aThis open access brief introduces the basic principles of control theory in a concise self-study guide. It complements the classic texts by emphasizing the simple conceptual unity of the subject. A novice can quickly see how and why the different parts fit together. The concepts build slowly and naturally one after another, until the reader soon has a view of the whole. Each concept is illustrated by detailed examples and graphics. The full software code for each example is available, providing the basis for experimenting with various assumptions, learning how to write programs for control analysis, and setting the stage for future research projects. The topics focus on robustness, design trade-offs, and optimality. Most of the book develops classical linear theory. The last part of the book considers robustness with respect to nonlinearity and explicitly nonlinear extensions, as well as advanced topics such as adaptive control and model predictive control. New students, as well as scientists from other backgrounds who want a concise and easy-to-grasp coverage of control theory, will benefit from the emphasis on concepts and broad understanding of the various approaches. 410 0$aSpringerBriefs in Applied Sciences and Technology,$x2191-5318 606 $aAutomatic control 606 $aSystem theory 606 $aControl theory 606 $aBiomathematics 606 $aMathematical physics 606 $aSocial sciences$xMathematics 606 $aControl and Systems Theory 606 $aSystems Theory, Control 606 $aMathematical and Computational Biology 606 $aMathematical Physics 606 $aMathematics in Business, Economics and Finance 615 0$aAutomatic control. 615 0$aSystem theory. 615 0$aControl theory. 615 0$aBiomathematics. 615 0$aMathematical physics. 615 0$aSocial sciences$xMathematics. 615 14$aControl and Systems Theory. 615 24$aSystems Theory, Control . 615 24$aMathematical and Computational Biology. 615 24$aMathematical Physics. 615 24$aMathematics in Business, Economics and Finance. 676 $a629.8 686 $aMAT003000$aSCI064000$aTEC004000$2bisacsh 700 $aFrank$b Steven A.$4aut$4http://id.loc.gov/vocabulary/relators/aut$00 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910293143503321 996 $aControl Theory Tutorial$92234747 997 $aUNINA