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Record Nr. |
UNINA9910476756003321 |
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Autore |
Nagahara Masaaki |
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Titolo |
Sparsity methods for systems and control / / Masaaki Nagahara |
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Pubbl/distr/stampa |
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Norwell, Massachusetts : , : Now Publishers, , [2020] |
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©2020 |
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Descrizione fisica |
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1 online resource (xvii, 241 pages) : illustrations |
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Collana |
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Disciplina |
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Soggetti |
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Automatic control - Design and construction |
Automatic control - Mathematical models |
Compressed sensing (Telecommunication) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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1. Introduction -- Part I: Sparse Representation for Vectors -- 2. What is Sparsity? -- 3. Curve Fitting and Sparse Optimization -- 4. Algorithms for Convex Optimization -- 5. Greedy Algorithms -- 6. Applications of Sparse Representation -- Part II: Sparsity Methods in Optimal Control -- 7. Dynamical Systems and Optimal Control -- 8. Maximum Hands-off Control -- 9. Numerical Optimization by Time Discretization -- 10. Advanced Topics. |
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Sommario/riassunto |
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The method of sparsity has been attracting a lot of attention in the fields related not only to signal processing, machine learning, and statistics, but also systems and control. The method is known as compressed sensing, compressive sampling, sparse representation, or sparse modeling. More recently, the sparsity method has been applied to systems and control to design resource-aware control systems. This book gives a comprehensive guide to sparsity methods for systems and control, from standard sparsity methods in finite-dimensional vector spaces (Part I) to optimal control methods in infinite-dimensional function spaces (Part II). The primary objective of this book is to show how to use sparsity methods for several engineering problems. For this, the author provides MATLAB programs by which the reader can try sparsity methods for themselves. Readers will obtain a deep understanding of sparsity methods by running these MATLAB |
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programs. Sparsity Methods for Systems and Control is suitable for graduate level university courses, though it should also be comprehendible to undergraduate students who have a basic knowledge of linear algebra and elementary calculus. Also, especially part II of the book should appeal to professional researchers and engineers who are interested in applying sparsity methods to systems and control. |
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