Ian R. Petersen

This is a unified collection of important recent results for the design of robust controllers for uncertain systems, primarily based on H8 control theory or its stochastic counterpart, risk sensitive control theory. Two practical applications are used to illustrate the methods throughout.

This is a unified collection of important recent results for the design of robust controllers for uncertain systems, primarily based on H8 control theory or its stochastic counterpart, risk sensitive control theory. Two practical applications are used to illustrate the methods throughout.

This monograph provides a state-of-the-art treatment of learning and robust control in quantum technology. It presents a systematic investigation of control design and algorithm realisation for several classes of quantum systems using control-theoretic tools and machine-learning methods. The approaches rely heavily on examples and the authors cover: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. Both theoretical algorithm design and potential practical applications are considered. Methods for enhancing robustness of performance are developed in the context of quantum state preparation, quantum gate construction, and ultrafast control of molecules. 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.

This monograph provides a state-of-the-art treatment of learning and robust control in quantum technology. It presents a systematic investigation of control design and algorithm realisation for several classes of quantum systems using control-theoretic tools and machine-learning methods. The approaches rely heavily on examples and the authors cover: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. Both theoretical algorithm design and potential practical applications are considered. Methods for enhancing robustness of performance are developed in the context of quantum state preparation, quantum gate construction, and ultrafast control of molecules. 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.

A significant shortcoming of the state space control theory that emerged in the 1960s was its lack of concern for the issue of robustness. However, in the design of feedback control systems, robustness is a critical issue. These facts led to great activity in the research area of robust control theory. One of the major developments of modern control theory was the Kalman Filter and hence the development of a robust version of the Kalman Filter has become an active area of research. Although the issue of robustness in filtering is not as critical as in feedback control (where there is always the issue of instability to worry about), research on robust filtering and state estimation has remained very active in recent years. However, although numerous books have appeared on the topic of Kalman filtering, this book is one of the first to appear on robust Kalman filtering. Most of the material presented in this book derives from a period of research collaboration between the authors from 1992 to 1994. However, its origins go back earlier than that. The first author (LR. P. ) became in­ terested in problems of robust filtering through his research collaboration with Dr. Duncan McFarlane. At this time, Dr. McFarlane was employed at the Melbourne Research Laboratories ofBHP Ltd. , a large Australian min­ erals, resources, and steel processing company.