Addresses the issue of large scale systems as they relate to robust control and linear matrix inequalities in a systematic manner
Discusses a new approach to applying Standard LMI techniques to large-scale systems, which combines graph-theoretic decomposition techniques with appropriate low-rank numerical approximations and dramatically reduces the computational effort
Provides numerous examples and a wide variety of applications, ranging from electric power systems and nonlinear circuits to mechanical problems and dynamic boolean networks
"Control of Complex Systems: Structural Constraints and Uncertainty" focuses on control design under information structure constraints, with a particular emphasis on large-scale systems. The complexity of such systems poses serious computational challenges and severely restricts the types of feedback laws that can be used in practice. This book systematically addresses the main issues, and provides a number of applications that illustrate potential design methods, most which use Linear Matrix Inequalities (LMIs), which have become a popular design tool over the past two decades. Authors Aleksandar I. Zecevic and Dragoslav D. Siljak use their years of experience in the control field to also:
- Address the issues of large-scale systems as they relate to robust control and linear matrix inequalities
- Discuss a new approach to applying standard LMI techniques to large-scale systems, combining graphic-theoretic decomposition techniques with appropriate low-rank numerical approximations and dramatically reducing the computational effort
- Providing numerous examples and a wide variety of applications, ranging from electric power systems and nonlinear circuits to mechanical problems and dynamic Boolean networks
"Control of Complex Systems: Structural Constraints and Uncertainty" will appeal to practicing engineers, researchers and students working in control design and other related areas.
Decompositions of Large-Scale Systems.- Information Structure Constraints.- Algebraic Constraints on the Gain Matrix.- Regions of Attraction.- Parametric Stability.- Future Directions: Dynamic Graphs.
Control of Complex Systems: Structural Constraints and Uncertainty focuses on control design under information structure constraints, with a particular emphasis on large-scale systems. The complexity of such systems poses serious computational challenges and severely restricts the types of feedback laws that can be used in practice. This book systematically addresses the main issues, and provides a number of applications that illustrate potential design methods, most which use Linear Matrix Inequalities (LMIs), which have become a popular design tool over the past two decades. Authors Aleksandar I. Zecevic and Dragoslav D. Siljak use their years of experience in the control field to also:
- Address the issues of large-scale systems as they relate to robust control and linear matrix inequalities
- Discuss a new approach to applying standard LMI techniques to large-scale systems, combining graphic-theoretic decomposition techniques with appropriate low-rank numerical approximations and dramatically reducing the computational effort
- Providing numerous examples and a wide variety of applications, ranging from electric power systems and nonlinear circuits to mechanical problems and dynamic Boolean networks
Control of Complex Systems: Structural Constraints and Uncertainty will appeal to practicing engineers, researchers and students working in control design and other related areas.
From the reviews:
"The monograph consisting of Preface, 6 Chapters, and Index is focused on control design under information structure constraints and uncertainty, with a particular emphasis on large-scale systems. ... The text is an excellent, clearly written, up-to-date authoritative reference on control of complex systems which is supplied with numerous examples and a wide variety of application studies. The monograph will appeal to graduate students, researchers, and practicing engineers acting in this challenging research area.” (Lubomír Bakule, Zentralblatt MATH, Vol. 1211, 2011)
"Control of Complex Systems: Structural Constraints and Uncertainty" focuses on control design under information structure constraints, with a particular emphasis on large-scale systems. The complexity of such systems poses serious computational challenges and severely restricts the types of feedback laws that can be used in practice. This book systematically addresses the main issues, and provides a number of applications that illustrate potential design methods, most which use Linear Matrix Inequalities (LMIs), which have become a popular design tool over the past two decades. Authors Aleksandar I. Zecevic and Dragoslav D. Siljak use their years of experience in the control field to also:
- Address the issues of large-scale systems as they relate to robust control and linear matrix inequalities
- Discuss a new approach to applying standard LMI techniques to large-scale systems, combining graphic-theoretic decomposition techniques with appropriate low-rank numerical approximations and dramatically reducing the computational effort
- Providing numerous examples and a wide variety of applications, ranging from electric power systems and nonlinear circuits to mechanical problems and dynamic Boolean networks
"Control of Complex Systems: Structural Constraints and Uncertainty" will appeal to practicing engineers, researchers and students working in control design and other related areas.
From the reviews:
"The monograph consisting of Preface, 6 Chapters, and Index is focused on control design under information structure constraints and uncertainty, with a particular emphasis on large-scale systems. ... The text is an excellent, clearly written, up-to-date authoritative reference on control of complex systems which is supplied with numerous examples and a wide variety of application studies. The monograph will appeal to graduate students, researchers, and practicing engineers acting in this challenging research area." (Lubomír Bakule, Zentralblatt MATH, Vol. 1211, 2011)
Inhaltsverzeichnis
Decompositions of Large-Scale Systems.- Information Structure Constraints.- Algebraic Constraints on the Gain Matrix.- Regions of Attraction.- Parametric Stability.- Future Directions: Dynamic Graphs.
Klappentext
"Control of Complex Systems: Structural Constraints and Uncertainty" focuses on control design under information structure constraints, with a particular emphasis on large-scale systems. The complexity of such systems poses serious computational challenges and severely restricts the types of feedback laws that can be used in practice. This book systematically addresses the main issues, and provides a number of applications that illustrate potential design methods, most which use Linear Matrix Inequalities (LMIs), which have become a popular design tool over the past two decades. Authors Aleksandar I. Zecevic and Dragoslav D. Siljak use their years of experience in the control field to also:
- Address the issues of large-scale systems as they relate to robust control and linear matrix inequalities
- Discuss a new approach to applying standard LMI techniques to large-scale systems, combining graphic-theoretic decomposition techniques with appropriate low-rank numerical approximations and dramatically reducing the computational effort
- Providing numerous examples and a wide variety of applications, ranging from electric power systems and nonlinear circuits to mechanical problems and dynamic Boolean networks
"Control of Complex Systems: Structural Constraints and Uncertainty" will appeal to practicing engineers, researchers and students working in control design and other related areas.
Addresses the issue of large scale systems as they relate to robust control and linear matrix inequalities in a systematic manner
Discusses a new approach to applying Standard LMI techniques to large-scale systems, which combines graph-theoretic decomposition techniques with appropriate low-rank numerical approximations and dramatically reduces the computational effort
Provides numerous examples and a wide variety of applications, ranging from electric power systems and nonlinear circuits to mechanical problems and dynamic boolean networks
Includes supplementary material: sn.pub/extras
