Linear matrix inequalities in system and control theory

By:

Boyd, Stephen

Contributor(s):

Material type: Text

TextSeries: SIAM Studies in Applied and Numerical Mathematics - 15Publication details: Philadelphia Society for Industrial and Applied Mathematics 1994Description: ix, 193pISBN:

9780898714852 (pbk.)

Subject(s):

DDC classification:

515.64 BOY

Summary: In this book the authors reduce a wide variety of problems arising in system and control theory to a handful of convex and quasiconvex optimization problems that involve linear matrix inequalities. These optimization problems can be solved using recently developed numerical algorithms that not only are polynomial-time but also work very well in practice; the reduction therefore can be considered a solution to the original problems. This book opens up an important new research area in which convex optimization is combined with system and control theory, resulting in the solution of a large number of previously unsolved problems.

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Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Plaksha University Library	Mathematics	515.64 BOY (Browse shelf(Opens below))	Available		002856

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Previous	515.35 SIM Differential equations : with applications and historical notes	515.352 NAY Applied nonlinear dynamics : analytical, computational, and experimental methods	515.53 TRI Generalized harmonic analysis and wavelet packets	515.64 BOY Linear matrix inequalities in system and control theory	515.64 SAS Nonlinear system : analysis, stability, and control	515.64 SAS Nonlinear system : analysis, stability, and control	515.723 CHU Inside the FFT black box : serial and parallel fast Fourier transform algorithms	Next

In this book the authors reduce a wide variety of problems arising in system and control theory to a handful of convex and quasiconvex optimization problems that involve linear matrix inequalities. These optimization problems can be solved using recently developed numerical algorithms that not only are polynomial-time but also work very well in practice; the reduction therefore can be considered a solution to the original problems. This book opens up an important new research area in which convex optimization is combined with system and control theory, resulting in the solution of a large number of previously unsolved problems.

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