In this paper, we present a linear matrix inequality （LMI）-based solution to implement H-two and H- infinity decentralized robust control strategies. Appropriate parametrization of optimal H-two and H-infinity contr...In this paper, we present a linear matrix inequality （LMI）-based solution to implement H-two and H- infinity decentralized robust control strategies. Appropriate parametrization of optimal H-two and H-infinity controllers is used. The general formulation of the decentralized control design leads to the optimal determination of both the state feedback gains and the observer gains of the decentralized controllers. This formulation is two folds： first, a centralized controller is obtained, and then, a simplified decentralized solution is derived by optimizing only the observer gains. The mathematical determination of these gains is formulated as an LMI optimization problem that can be easily solved using LMI solvers. As an experimental evaluation of these controllers, a real time application to an aerothermic process is carried out. A continuous-time model of the process obtained with a suitable direct continuous-time identification approach is elaborated. Results illustrating the real performance obtained from the H-two and H-infinity decentralized controllers are di^cu^ge.d and comnare, d with th~ ce^ntraliTed nn^g展开更多
With over 10 million points of genetic variation from person to person, every individual’s genome is unique and provides a highly reliable form of identification. This is because the genetic code is specific to each ...With over 10 million points of genetic variation from person to person, every individual’s genome is unique and provides a highly reliable form of identification. This is because the genetic code is specific to each individual and does not change over time. Genetic information has been used to identify individuals in a variety of contexts, such as criminal investigations, paternity tests, and medical research. In this study, each individual’s genetic makeup has been formatted to create a secure, unique code that incorporates various elements, such as species, gender, and the genetic identification code itself. The combinations of markers required for this code have been derived from common single nucleotide polymorphisms (SNPs), points of variation found in the human genome. The final output is in the form of a 24 numerical code with each number having three possible combinations. The custom code can then be utilized to create various modes of identification on the decentralized blockchain network as well as personalized services and products that offer users a novel way to uniquely identify themselves in ways that were not possible before.展开更多
文摘In this paper, we present a linear matrix inequality （LMI）-based solution to implement H-two and H- infinity decentralized robust control strategies. Appropriate parametrization of optimal H-two and H-infinity controllers is used. The general formulation of the decentralized control design leads to the optimal determination of both the state feedback gains and the observer gains of the decentralized controllers. This formulation is two folds： first, a centralized controller is obtained, and then, a simplified decentralized solution is derived by optimizing only the observer gains. The mathematical determination of these gains is formulated as an LMI optimization problem that can be easily solved using LMI solvers. As an experimental evaluation of these controllers, a real time application to an aerothermic process is carried out. A continuous-time model of the process obtained with a suitable direct continuous-time identification approach is elaborated. Results illustrating the real performance obtained from the H-two and H-infinity decentralized controllers are di^cu^ge.d and comnare, d with th~ ce^ntraliTed nn^g
文摘With over 10 million points of genetic variation from person to person, every individual’s genome is unique and provides a highly reliable form of identification. This is because the genetic code is specific to each individual and does not change over time. Genetic information has been used to identify individuals in a variety of contexts, such as criminal investigations, paternity tests, and medical research. In this study, each individual’s genetic makeup has been formatted to create a secure, unique code that incorporates various elements, such as species, gender, and the genetic identification code itself. The combinations of markers required for this code have been derived from common single nucleotide polymorphisms (SNPs), points of variation found in the human genome. The final output is in the form of a 24 numerical code with each number having three possible combinations. The custom code can then be utilized to create various modes of identification on the decentralized blockchain network as well as personalized services and products that offer users a novel way to uniquely identify themselves in ways that were not possible before.
