A robust observer for performing power system dynamic state estimation (DSE) of a synchronous generator is proposed. The observer is developed using the concept of $\mathcal{L}_{\infty}$ stability for uncertain, nonlinear dynamic generator models. We use this concept to (i) design a simple, scalable, and robust dynamic state estimator and (ii) obtain a performance guarantee on the state estimation error norm relative to the magnitude of uncertainty from unknown generator inputs, and process and measurement noises. Theoretical methods to obtain upper and lower bounds on the estimation error are also provided. Numerical tests validate the performance of the $\mathcal{L}_{\infty}$-based estimator in performing DSE under various scenarios. The case studies reveal that the derived theoretical bounds are valid for a variety of case studies and operating conditions, while yielding better performance than existing power system DSE methods.
Gradient Networks for Universal Magnetic Modeling of Synchronous Machines
Department of Electrical Engineering and Automation, Aalto University（电气工程与自动化系，阿alto大学）；Aalto University House of AI（阿alto大学人工智能学院）；Research Council of Finland Centre of Excellence in High-Speed Electromechanical Energy Conversion Systems（芬兰研究理事会高速电磁能量转换系统卓越中心）；Aalto School of Electrical Engineering（阿alto电气工程学院）；ABB Oy, Drives（ABB Oy，驱动部门）
Synchronous Observer Design for Landmark-Inertial SLAM with Magnetometer and Intermittent GNSS Measurements
Centre for Systems and Control, Indian Institute of Technology Bombay（印度理工学院孟买分校系统与控制中心）；School of Aerospace, Mechanical and Mechatronic Engineering (AMME), Faculty of Engineering, University of Sydney（悉尼大学工程学院航空航天、机械与机电工程系）
Beyond Asymptotics: Targeted exploration with finite-sample guarantees
Institute for Systems Theory and Automatic Control, University of Stuttgart（斯图加特大学系统与自动控制中心）；Institute for Dynamic Systems and Control, ETH Zürich（苏黎世联邦理工学院动态系统与控制研究所）
