000			04469nam a22006375i 4500
001			978-3-319-50790-3
003			DE-He213
005			20210118142629.0
007			cr nn 008mamaa
008			161224s2017 gw | s |||| 0|eng d
020			_a9783319507903 _9978-3-319-50790-3
024	7		_a10.1007/978-3-319-50790-3 _2doi
050		4	_aTJ212-225
072		7	_aTJFM _2bicssc
072		7	_aTEC004000 _2bisacsh
072		7	_aTJFM _2thema
082	0	4	_a629.8 _223
100	1		_aScheinker, Alexander. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aModel-Free Stabilization by Extremum Seeking _h[electronic resource] / _cby Alexander Scheinker, Miroslav Krstić.
250			_a1st ed. 2017.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2017.
300			_aIX, 127 p. 46 illus., 33 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Control, Automation and Robotics, _x2192-6786
505	0		_aIntroduction -- Weak Limit Averaging for Studying the Dynamics of Extremum-Seeking-Stabilized Systems -- Minimization of Lyapunov Functions -- Control Affine Systems -- Non-C2 Extremum Seeking -- Bounded Extremum Seeking -- Extremum Seeking for Stabilization of Systems Not Affine in Control -- General Choice of Extremum-Seeking Dithers -- Application Study: Particle Accelerator Tuning.
520			_aWith this brief, the authors present algorithms for model-free stabilization of unstable dynamic systems. An extremum-seeking algorithm assigns the role of a cost function to the dynamic system’s control Lyapunov function (clf) aiming at its minimization. The minimization of the clf drives the clf to zero and achieves asymptotic stabilization. This approach does not rely on, or require knowledge of, the system model. Instead, it employs periodic perturbation signals, along with the clf. The same effect is achieved as by using clf-based feedback laws that profit from modeling knowledge, but in a time-average sense. Rather than use integrals of the systems vector field, we employ Lie-bracket-based (i.e., derivative-based) averaging. The brief contains numerous examples and applications, including examples with unknown control directions and experiments with charged particle accelerators. It is intended for theoretical control engineers and mathematicians, and practitioners working in various industrial areas and in robotics.
650		0	_aControl engineering.
650		0	_aSystem theory.
650		0	_aCalculus of variations.
650		0	_aParticle acceleration.
650		0	_aArtificial intelligence.
650	1	4	_aControl and Systems Theory. _0http://scigraph.springernature.com/things/product-market-codes/T19010
650	2	4	_aSystems Theory, Control. _0http://scigraph.springernature.com/things/product-market-codes/M13070
650	2	4	_aCalculus of Variations and Optimal Control; Optimization. _0http://scigraph.springernature.com/things/product-market-codes/M26016
650	2	4	_aParticle Acceleration and Detection, Beam Physics. _0http://scigraph.springernature.com/things/product-market-codes/P23037
650	2	4	_aArtificial Intelligence. _0http://scigraph.springernature.com/things/product-market-codes/I21000
700	1		_aKrstić, Miroslav. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319507897
776	0	8	_iPrinted edition: _z9783319507910
830		0	_aSpringerBriefs in Control, Automation and Robotics, _x2192-6786
856	4	0	_uhttps://doi.org/10.1007/978-3-319-50790-3
912			_aZDB-2-ENG
999			_c450780 _d450780
942			_cEB
506			_aAvailable to subscribing member institutions only. Доступно лише організаціям членам підписки.
506			_fOnline access from local network of NaUOA.
506			_fOnline access with authorization at https://link.springer.com/
506			_fОнлайн-доступ з локальної мережі НаУОА.
506			_fОнлайн доступ з авторизацією на https://link.springer.com/