Learning and Robust Control in Quantum Technology / Communications and Control Engineering (PDF)
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- sliding mode control of quantum systems;
- control and classification of inhomogeneous quantum ensembles using sampling-based learning control;
- robust and optimal control design using machine-learning methods;
- robust stability of quantum systems; and
- H8 and fault-tolerant control of quantum systems.
Researchers and graduates studying systems and control theory, quantum control, and quantum engineering, especially from backgrounds in electrical engineering, applied mathematics and quantum information will find Learning and Robust Control in Quantum Technology to be a valuable reference for the investigation of learning and robust control of quantum systems. The material contained in this book will also interest chemists and physicists working on chemical physics, quantum optics, and quantum information technology.
Ian R. Petersen is currently a professor at the Australian National University. He held an Australian Research Council Professorial Fellowship from 2005 to 2007, an Australian Research Council Federation Fellowship from 2007 to 2012, and an Australian Research Council Laureate Fellowship from 2012 to 2016. He has served as an Associate Editor for the IEEE Transactions on Automatic Control, Systems and Control Letters, Automatica, and SIAM Journal on Control and Optimization. Currently he is an Editor for Automatica in the area of optimization in systems and control. He is a fellow of the IFAC, the IEEE and the Australian Academy of Science. His main research interests are in robust control theory, quantum control theory and stochastic control theory. Ian Petersen was elected IFAC Council Member for the 2014-2017 and 2018-2021 Trienniums. He was also elected to be a member of the IEEE Control Systems Society Board of Governors for the periods 2011-2013 and 2015-2017. He was Vice-president for Technical Activity for the Asian Control Association and was
- Autoren: Daoyi Dong , Ian R. Petersen
- 2023, 2023, 252 Seiten, Englisch
- Verlag: Springer Nature Switzerland
- ISBN-10: 3031202457
- ISBN-13: 9783031202452
- Erscheinungsdatum: 24.03.2023
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