000			04189cam a2200577 i 4500
001			9781003160700
003			FlBoTFG
005			20240213122825.0
006			m o d
007			cr cnu|||unuuu
008			230307s2023 flua ob 001 0 eng d
040			_aOCoLC-P _beng _erda _epn _cOCoLC-P
020			_a9781003160700 _q(electronic bk.)
020			_a1003160700 _q(electronic bk.)
020			_a9781000860290 _q(electronic bk. : EPUB)
020			_a1000860299 _q(electronic bk. : EPUB)
020			_z9780367746599
020			_a9781000860276 _q(electronic bk. : PDF)
020			_a1000860272 _q(electronic bk. : PDF)
020			_z9780367750084
024	7		_a10.1201/9781003160700 _2doi
035			_a(OCoLC)1372013426
035			_a(OCoLC-P)1372013426
050		4	_aTJ213
072		7	_aCOM _x059000 _2bisacsh
072		7	_aMAT _x003000 _2bisacsh
072		7	_aMED _x009000 _2bisacsh
072		7	_aTRC _2bicssc
082	0	4	_a629.80285 _223/eng/20230316
100	1		_aWang, Jianhong _c(Engineering researcher), _eauthor.
245	1	0	_aData driven strategies : _btheory and applications / _cWang Jianhong, Ricardo A. Ramirez-Mendoza, Ruben Morales-Menendez.
250			_aFirst edition.
264		1	_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c2023.
300			_a1 online resource : _billustrations
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
505	0		_aIntroduction. Data driven model predictive control. Data driven identification for closed loop system. Data driven model validation for closed loop system. Data driven identification for nonlinear system. Data driven iterative tuning control. Data driven applications. Data driven subspace prediction control. Conclusions and outlook.
520			_a"One of the main problems in science and engineering is to provide a quantitative description of the systems under investigation, leveraging collected noisy data. Such a description may be a complete mathematical model or a mechanism to return controllers corresponding to new, unseen inputs. Recent advances in the theories are described in detail, along with their applications in engineering. The book aims to develop model-free system analysis and control strategies, i.e., data-driven control from theoretical analysis and engineering applications based only on measured data. The study aims to develop system identification, and combination in advanced control theory, i.e., data-driven control strategy as system and controller are generated from measured data directly. The book covers the development of system identification and its combination in advanced control theory, i.e., data-driven control strategy, as they all depend on measured data. Firstly, data-driven identification is developed for the closed-loop, nonlinear system and model validation, i.e., obtaining model descriptions from measured data. Secondly, the data-driven idea is combined with some control strategies to be considered data-driven control strategies, such as data-driven model predictive control, data-driven iterative tuning control, and data-driven subspace predictive control. Thirdly data-driven identification and data-driven control strategies are applied to interested engineering. In this context, the book provides algorithms to perform state estimation of dynamical systems from noisy data and some convex optimization algorithms through identification and control problems"-- _cProvided by publisher.
588			_aOCLC-licensed vendor bibliographic record.
650		7	_aCOMPUTERS / Computer Engineering _2bisacsh
650		7	_aMATHEMATICS / Applied _2bisacsh
650		7	_aMEDICAL / Biotechnology _2bisacsh
650		0	_aAutomatic control _xData processing.
650		0	_aSystem design _xData processing.
650		0	_aSystems engineering _xData processing.
700	1		_aRamírez-Mendoza, Ricardo A., _eauthor.
700	1		_aMorales-Menéndez, Rubén, _eauthor.
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781003160700
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999			_c4927 _d4927