000 04472nam a22005055i 4500
001 978-3-319-05639-5
003 DE-He213
005 20200421111848.0
007 cr nn 008mamaa
008 140607s2014 gw | s |||| 0|eng d
020 _a9783319056395
_9978-3-319-05639-5
024 7 _a10.1007/978-3-319-05639-5
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aBenzaouia, Abdellah.
_eauthor.
245 1 0 _aAdvanced Takagi‒Sugeno Fuzzy Systems
_h[electronic resource] :
_bDelay and Saturation /
_cby Abdellah Benzaouia, Ahmed El Hajjaji.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXXXII, 294 p. 71 illus., 66 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Systems, Decision and Control,
_x2198-4182 ;
_v8
505 0 _aIntroduction to Takagi‒Sugeno Fuzzy Systems -- Stabilization of Takagi‒Sugeno Fuzzy Systems with Constrained Controls -- Static Output Feedback Control for Fuzzy Systems -- Stabilization of Discrete-time Takagi‒Sugeno Fuzzy Positive Systems -- Stabilization of Delayed T-S Fuzzy Positive Systems -- Robust Control of T-S Fuzzy Systems with Time-varying Delay -- Robust Output H¥ Fuzzy Control.-Stabilization of Discrete-time T-S Fuzzy Positive Systems with Multiple Delays -- Stabilization of Two Dimensional T-S Fuzzy Systems.
520 _aThis monograph puts the reader in touch with a decade's worth of new developments in the field of fuzzy control specifically those of the popular Takagi-Sugeno (T-S) type. New techniques for stabilizing control analysis and design based on multiple Lyapunov functions and linear matrix inequalities (LMIs), are proposed. All the results are illustrated with numerical examples and figures and a rich bibliography is provided for further investigation. Control saturations are taken into account within the fuzzy model. The concept of positive invariance is used to obtain sufficient asymptotic stability conditions for the fuzzy system with constrained control inside a subset of the state space. The authors also consider the non-negativity of the states. This is of practical importance in many chemical, physical and biological processes that involve quantities that have intrinsically constant and non-negative sign: concentration of substances, level of liquids, etc. Results for linear systems are then extended to linear systems with delay. It is shown that LMI techniques can usually handle the new constraint of non-negativity of the states when care is taken to use an adequate Lyapunov function. From these foundations, the following further problems are also treated: �        asymptotic stabilization of uncertain T-S fuzzy systems with time-varying delay, focusing on delay-dependent stabilization synthesis based on parallel distributed controller (PDC); �        asymptotic stabilization of uncertain T-S fuzzy systems with multiple delays, focusing on delay-dependent stabilization synthesis based on PDC with results obtained under linear programming; �        design of delay-independent, observer-based, H-infinity control for T-S fuzzy systems with time varying delay; and �        asymptotic stabilization of 2-D T-S fuzzy systems. Advanced Takagi-Sugeno Fuzzy Systems provides researchers and graduate students interested in fuzzy control systems with further approaches based LMI and LP.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aComputational intelligence.
650 0 _aControl engineering.
650 1 4 _aEngineering.
650 2 4 _aControl.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aComputational Intelligence.
700 1 _aEl Hajjaji, Ahmed.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319056388
830 0 _aStudies in Systems, Decision and Control,
_x2198-4182 ;
_v8
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-05639-5
912 _aZDB-2-ENG
942 _cEBK
999 _c55916
_d55916