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008			220301s2022 sz | s |||| 0|eng d
020			_a9783030971021
024	7		_a10.1007/978-3-030-97102-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTJ217 _b2022 EB
100	1		_aMaiti, Roshni _eautor _9687133
245	1	0	_aHybrid L1 Adaptive Control : _bApplications of Fuzzy Modeling, Stochastic Optimization and Metaheuristics _cby Roshni Maiti, Kaushik Das Sharma, Gautam Sarkar
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XLII, 234 páginas) _b167 ilustraciones, 150 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aStudies in Systems Decision and Control _x2198-4190 _v422
505	0		_aIntroduction -- Basic L1 Adaptive Controller: A State Of The Art Study -- Hybrid L1 Adaptive Controller- I: Stochastic Optimization & Metaheuristics Based Approach -- Hybrid L1 Adaptive Controller- II: Fuzzy Parallel Distributed Compensation Based Approach -- Speed Control Of Electrical Actuator -- Angular Position Control Of Two Link Robot Manipulator -- Temperature Control Of Air Heater System -- Future Research Directions Of Hybrid Controller.
520			_aThis book details the designing of hybrid control strategies for practical systems containing time varying uncertainties, disturbances, nonlinearities, unknown parameters, unmodelled dynamics, delays, etc., concurrently. In this book, the advantages of different controllers will be brought together to produce superior control performance for the practical systems. Being aware of the advantages of adaptive controller to tackle unknown constant, time varying uncertainties and time varying disturbances, a variant of adaptive controller, namely L1 adaptive controller, is hybridized with other strategies. In this book, to facilitate optimal parameter setting of the basic L1 adaptive controller, stochastic optimization technique will be hybridized with it. The stability of the optimization technique along with the controller will be guaranteed analytically with the help of spectral radius convergence. The proposed method exhibits satisfactory exploration and exploitation capabilities. Again, this book will throw light on tackling nonlinearities along with uncertainties and disturbances by hybridizing fuzzy logic with L1 adaptive controller. The performances of the designed controllers will be compared with different control methodologies to validate their effectiveness. The overall stability of the nonlinear system with the designed controller will be guaranteed with the help of fuzzy Lyapunov function to retain the zonal behaviour of the system. This fuzzy PDC-L1 adaptive controller is efficient to tackle nonlinearities and at the same time cancels unknown constant, time varying uncertainties and time varying disturbances adequately. This book will also contain four simulation case studies to validate fruitfulness of the designed controllers. To demonstrate the superior control ability of these controllers in tackling practical system, three experimental case studies will also be provided.
988			_aSpringer_Robotics_2022
650		7	_2embne _9407082 _aSistemas de control inteligente
776	0	8	_iPrinted edition: _z9783030971014
776	0	8	_iPrinted edition: _z9783030971038
776	0	8	_iPrinted edition: _z9783030971045
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi-org.ezproxy.universidadeuropea.es/10.1007/978-3-030-97102-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _eu _zSI