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 ther 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. Get A Copy.
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lems arising in system and control theory to a few standard convex or quasiconvex optimization problems involving linear matrix inequalities (LMIs). Since these. Linear Matrix Inequalities in System and Control Theory. LMIs in System & Control Theory book cover. Linear Matrix Inequalities in System and Control Theory.
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Brand new Book. There are many robust techniques well known in structural control literature, as for instance, Moreira et al. Control 72 , Therefore, the synthesis of a low order plant is fundamental for a controller success. The sensor position candidates consider all nodes on vertical direction. Both delay-independent and delay-dependent results are reported in the article.
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Series: Studies in Applied and Numerical Mathematics. Buy the Print Edition. Keywords: matrix inequalities , convex optimization , control theory , interior-point methods. Return to All Sections.
Front Matter. Some Matrix Problems. Linear Differential Inclusions. Lur'e and Multiplier Methods. Systems with Multiplicative Noise. Miscellaneous Problems.