Adaptive Inverse Control: A Signal Processing Approach, by Mohamed E. El?Hawary(eds.)

By Mohamed E. El?Hawary(eds.)

A self-contained advent to adaptive inverse control

Now that includes a revised preface that emphasizes the assurance of either keep an eye on platforms and sign processing, this reissued variation of Adaptive Inverse keep watch over takes a singular technique that isn't on hand in the other book.

Written by way of pioneers within the box, Adaptive Inverse keep an eye on provides tools of adaptive sign processing which are borrowed from the sector of electronic sign processing to resolve difficulties in dynamic structures regulate. This special approach permits engineers in either fields to proportion instruments and methods. truly and intuitively written, Adaptive Inverse regulate illuminates idea with an emphasis on useful purposes and common sense knowing. It covers: the adaptive inverse regulate proposal; Weiner filters; adaptive LMS filters; adaptive modeling; inverse plant modeling; adaptive inverse keep watch over; different configurations for adaptive inverse keep watch over; plant disturbance canceling; approach integration; Multiple-Input Multiple-Output (MIMO) adaptive inverse keep an eye on structures; nonlinear adaptive inverse regulate structures; and more.

whole with a thesaurus, an index, and bankruptcy summaries that consolidate the data offered, Adaptive Inverse regulate is acceptable as a textbook for complex undergraduate- and graduate-level classes on adaptive keep watch over and in addition serves as a helpful source for practitioners within the fields of keep watch over structures and sign processing.Content:
Chapter 1 The Adaptive Inverse regulate notion (pages 1–39):
Chapter 2 Wiener Filters (pages 40–58):
Chapter three Adaptive LMS Filters (pages 59–87):
Chapter four Adaptive Modeling (pages 88–110):
Chapter five Inverse Plant Modeling (pages 111–137):
Chapter 6 Adaptive Inverse keep an eye on (pages 138–159):
Chapter 7 different Configurations for Adaptive Inverse regulate (pages 160–208):
Chapter eight Plant Disturbance Canceling (pages 209–257):
Chapter nine procedure Integration (pages 258–269):
Chapter 10 Multiple?Input Multiple?Output (MIMO) Adaptive Inverse regulate platforms (pages 270–302):
Chapter eleven Nonlinear Adaptive Inverse keep an eye on (pages 303–329):
Chapter 12 friendly Surprises (pages 330–338):

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Additional info for Adaptive Inverse Control: A Signal Processing Approach, Reissue Edition

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42) To evaluate this z-transform, examine the geometric autocorrelation function pictured in Fig. 5, given by &,(rn) = A t i m 1 , where A is a scale factor, and t is a geometric ratio less than one. 3),the transform of the autocorrelation function of Fig. 5 can be expressed as 2 m=-rn + r z - ’ + r2z-2 + r3z-3 + . ] + A [ r z + r 2 z 2+ r 3 z 3+ . . I . 43) Sec. 6 49 Region ctt coniergence for geometric autocorrelation fuiiction The two sums are geometric and converge for certain values of 2.

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R. and A. KEZER,“New developmentsin thedesignof adaptivecontrol systems,” Paper No. 6 1-39, Institute of Aeronautical Sciences, February 1961. F. D. N , P ~ W E I ,and L , A. EMAMI-NAEINI. : Addison-Wesley, 1986). F. D. L. WORKMAN, Digital control of dynamic systems, 2nd ed. : Addison-Wesley. 1990). [92) K . OCATA,Modern control engineering, 2nd cd. (Englewood Cliffs: Prentice Hall, 1990). F. SPECHT, “Generation of polynomial discriminant functions for pattern recogni- tion,” IEEE Trans. on Electronic Computers.

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