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710	2		_aSpringerLink (Online service) _9106996
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008			190316s2019 gw a o |||| 0|eng d
020			_a9783030118693
024	7		_a10.1007/978-3-030-11869-3 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aTA169 _b2019 EB
100	1		_aPatan, Krzysztof _eautor _9671066
245	1	0	_aRobust and fault-tolerant control : _bneural-network-based solutions _cby Krzysztof Patan
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2019
300			_a1 recurso en línea (XXVIII, 209 páginas) _b118 ilustraciones, 25 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF _2rda
490	0		_aStudies in Systems Decision and Control _x2198-4182 _v197
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aIntroduction -- Neural Networks -- Robust and Fault-Tolerant Control -- Model Predictive Control -- Control Reconfiguration -- Iterative Learning Control -- Concluding Remarks and Further Research Directions.
520	3		_aRobust and Fault-Tolerant Control proposes novel automatic control strategies for nonlinear systems developed by means of artificial neural networks and pays special attention to robust and fault-tolerant approaches. The book discusses robustness and fault tolerance in the context of model predictive control, fault accommodation and reconfiguration, and iterative learning control strategies. Expanding on its theoretical deliberations the monograph includes many case studies demonstrating how the proposed approaches work in practice. The most important features of the book include: a comprehensive review of neural network architectures with possible applications in system modelling and control; a concise introduction to robust and fault-tolerant control; step-by-step presentation of the control approaches proposed; an abundance of case studies illustrating the important steps in designing robust and fault-tolerant control; and a large number of figures and tables facilitating the performance analysis of the control approaches described. The material presented in this book will be useful for researchers and engineers who wish to avoid spending excessive time in searching neural-network-based control solutions. It is written for electrical, computer science and automatic control engineers interested in control theory and their applications. This monograph will also interest postgraduate students engaged in self-study of nonlinear robust and fault-tolerant control.
988			_aPrimersemestre_2019_Robotics
650		7	_2embne _aFiabilidad (Ingeniería) _9141577
650		7	_2embne _9668452 _aTolerancia a los fallos (Informática)
650		7	_2embne _aRedes neuronales artificiales _9678664
776	0	8	_iPrinted edition: _z9783030118686
776	0	8	_iPrinted edition: _z9783030118709
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-11869-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aSI _cm _dz _feng _ggw _h0 _b10/2019 _eel _zSI