Uncertain Information And Linear Systems


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Uncertain Information and Linear Systems


Uncertain Information and Linear Systems

Author: Tofigh Allahviranloo

language: en

Publisher: Springer Nature

Release Date: 2019-09-23


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This book identifies the important uncertainties to use in real-world problem modeling. Having information about several types of ambiguities, vagueness, and uncertainties is vital in modeling problems that involve linguistic variables, parameters, and word computing. Today, since most of our real-world problems are related to decision-making at the right time, we need to apply intelligent decision science. Clearly, in order to have an appropriate and flexible mathematical model, every intelligent system requires real data on our environment. Presenting problems that can be represented using mathematical models to create a system of linear equations, this book discusses the latest insights into uncertain information.

Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems


Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems

Author: Xiao-Heng Chang

language: en

Publisher: Springer

Release Date: 2016-08-23


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"Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique. Though primarily intended for graduate students in control and filtering, the book can also serve as a valuable reference work for researchers wishing to explore the area of robust H-infinity control and filtering of uncertain systems. Dr. Xiao-Heng Chang is a Professor at the College of Engineering, Bohai University, China.

Uncertain Information and Linear Systems


Uncertain Information and Linear Systems

Author: Tofigh Allahviranloo

language: en

Publisher:

Release Date: 2020


DOWNLOAD





This book identifies the important uncertainties to use in real-world problem modeling. Having information about several types of ambiguities, vagueness, and uncertainties is vital in modeling problems that involve linguistic variables, parameters, and word computing. Today, since most of our real-world problems are related to decision-making at the right time, we need to apply intelligent decision science. Clearly, in order to have an appropriate and flexible mathematical model, every intelligent system requires real data on our environment. Presenting problems that can be represented using mathematical models to create a system of linear equations, this book discusses the latest insights into uncertain information.