000			03577nam a2200397za04500
001			17509
008			050703s2011 gw eng d
020			_a9783642167768 99783642167768
050			_aQ342
082			_a006.3 _b223
100			_aLendek, Zsófia. _eauthor.
245			_aStability Analysis and Nonlinear Observer Design Using Takagi-Sugeno Fuzzy Models _h[electronic resource] / _cby Zsófia Lendek, Thierry Marie Guerra, Robert Babuska, Bart Schutter.
300			_aX, 198 p. _bonline resource.
336			_atext _btxt 2rdacontent
337			_acomputer _bc 2rdamedia
338			_aonline resource _bcr 2rdacarrier
490			_aStudies in Fuzziness and Soft Computing
490			_x-1434-9922 ; _v-262
505			_aIntroduction -- Takagi-Sugeno fuzzy models -- Stability analysis of TS fuzzy systems -- Observers for TS fuzzy systems -- Cascaded TS systems and observers -- Distributed TS systems and observers -- Adaptive observers for TS systems.
520			_aMany problems in decision making, monitoring, fault detection, and control require the knowledge of state variables and time-varying parameters that are not directly measured by sensors. In such situations, observers, or estimators, can be employed that use the measured input and output signals along with a dynamic model of the system in order to estimate the unknown states or parameters. An essential requirement in designing an observer is to guarantee the convergence of the estimates to the true values or at least to a small neighborhood around the true values. However, for nonlinear, large-scale, or time-varying systems, the design and tuning of an observer is generally complicated and involves large computational costs. This book provides a range of methods and tools to design observers for nonlinear systems represented by a special type of a dynamic nonlinear modelá- the Takagi-Sugeno (TS) fuzzy model. The TS model is a convex combination of affine linear models, which facilitates its stability analysis and observer design by using effective algorithms based on Lyapunov functions and linear matrix inequalities. Takagi-Sugeno models are known to be universal approximators and, in addition, a broad class of nonlinear systems can be exactly represented as a TS system. Three particular structures of large-scale TS models are considered: cascaded systems, distributed systems, and systems affected by unknown disturbances. The reader will find in-depth theoretic analysis accompanied by illustrative examples and simulations of real-world systems. Stability analysis of TS fuzzy systems is addressed in detail. The intended audience are graduate students and researchers both from academia and industry. For newcomers to the field, the book provides a concise introduction dynamic TS fuzzy models along with two methods to construct TS models for a given nonlinear system. For additional information, see the book website at http://www.dcsc.tudelft.nl/fuzzybook/
650			_aEngineering.
650			_aArtificial intelligence.
650			_aEngineering.
650			_aComputational Intelligence.
650			_aArtificial Intelligence (incl. Robotics).
700			_aGuerra, Thierry Marie.
700			_eauthor.
700			_aBabuska, Robert.
700			_eauthor.
700			_aSchutter, Bart.
700			_eauthor.
710			_aSpringerLink (Online service)
773			_a0# _tSpringer eBooks
856			_uhttp://bibliotecavirtual.escuelaing.edu.co:2120/book/10.1007/978-3-642-16776-8 _yir a documento _qURL
942			_2ddc _cCF
999			_c14134 _d14134