000			04112nam a22004094u 4500
001			10.1002/9781119847533
003			Wiley
005			20251030120318.0
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008			240923t2024||||xxu fs| |0|| 0|eng||
020			_a9781119847533 _qelectronic
024	7		_a10.1002/9781119847533 _2doi
041			_aeng
245	0	0	_aLinear and Nonlinear System Modeling _h[electronic resource] _cEdited by Tamal Roy, Suman Lata Tripathi, Souvik Ganguli.
250			_a1
260			_bWiley _c2024
264		1	_bWiley _c2024
300			_a240pp.;
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _2rdaft
347			_bPDF
520			_aWritten and edited by a team of experts in the field, this exciting new volume presents the cutting-edge techniques, latest trends, and state-of-the-art practical applications in linear and nonlinear system modeling. Mathematical modeling of control systems is, essentially, extracting the essence of practical problems into systematic mathematical language. In system modeling, mathematical expression deals with modeling and its applications. It is characterized that how a modeling competency can be categorized and its activity can contribute to building up these competencies. Mathematical modeling of a practical system is an attractive field of research and an advanced subject with a variety of applications. The main objective of mathematical modeling is to predict the behavior of the system under different operating conditions and to design and implement efficient control strategies to achieve the desired performance. A considerable effort has been directed to the development of models, which must be understandable and easy to analyze. It is a very difficult task to develop mathematical modeling of complicated practical systems considering all its possible high-level non-linearity and cross couple dynamics. Although mathematical modeling of nonlinear systems sounds quite interesting, it is difficult to formulate the general solution to analyze and synthesize nonlinear dynamical systems. Most of the natural processes are nonlinear, having very high computational complexity of several numerical issues. It is impossible to create any general solution or individual procedure to develop exact modeling of a non-linear system, which is often improper and too complex for engineering practices. Therefore, some series of approximation procedures are used, in order to get some necessary knowledge about the nonlinear system dynamics. There are several complicated mathematical approaches for solving these types of problems, such as functional analysis, differential geometry or the theory of nonlinear differential equations.
650		4	_aSystems Engineering & Management
650		4	_aElectric Power Systems _991547
650		4	_aMaterials for Energy Systems
653	0	0	_a<p>Model order reduction; Time delay systems; Fractional order systems; Unstable systems; Non-minimum phase systems; Interval systems; Chemical process modelling; Nonlinear systems; Linear time-invariant systems; Modelling of power system network; Modelling of power converters; Control systems; Traditional control algorithms; Intelligent control; Single-input single-output systems; Single-input multi-output systems; Multi-input single-output systems; Multi-input multi-output systems; Electronic system modelling; Boiler plant modelling; Nuclear power plant modelling; Hydro plant modelling</p>
700	1		_aRoy, Tamal _4edt _992119
700	1		_aTripathi, Suman Lata _4edt
700	1		_aGanguli, Souvik _4edt _991648
776	0	8	_iPrinted edition: _z9781119847427
856	4	0	_uhttps://doi.org/10.1002/9781119847533 _aWiley Online Library
856	4	0	_uhttps://onlinelibrary.wiley.com/action/showBook?doi=10.1002%2F9781119847533 _aWiley Online Library
856	4	2	_3Cover Image _uhttps://onlinelibrary.wiley.com/cms/asset/5107694e-82d7-47ed-83d6-fe73b2b510b3/9781119847533.cover.gif _aWiley Online Library
999			_c67225 _d67225