Results 281 to 290 of about 1,063,107 (310)
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Modularized data-driven approximation of the Koopman operator and generator
arXiv.orgExtended Dynamic Mode Decomposition (EDMD) is a widely-used data-driven approach to learn an approximation of the Koopman operator. Consequently, it provides a powerful tool for data-driven analysis, prediction, and control of nonlinear dynamical ...
Yang Guo +3 more
semanticscholar +1 more source
IEEE/RJS International Conference on Intelligent RObots and Systems
Highly dynamic maneuvers pose a challenge to conventional state estimators of quadrotors in rapidly tracking the pose. This paper proposes a data-driven Koopman operator-based error-state Kalman filter (K-ESKF) to enhance pose estimation in agile flight.
Peng Huang +2 more
semanticscholar +1 more source
Highly dynamic maneuvers pose a challenge to conventional state estimators of quadrotors in rapidly tracking the pose. This paper proposes a data-driven Koopman operator-based error-state Kalman filter (K-ESKF) to enhance pose estimation in agile flight.
Peng Huang +2 more
semanticscholar +1 more source
Model Predictive Traction Control System Based on the Koopman Operator
International Conference on System Theory, Control and ComputingDue to their importance, traction control and antilock braking systems have become standard equipment in modern vehicles. However, accurate models of tire dynamics are often difficult to obtain and usually include nonlinearities, making their use in ...
Josip Kir Hromatko, Š. Ileš
semanticscholar +1 more source
American Control Conference
Theoretical properties and data-driven learning of the Koopman operator, which represents nonlinear dynamics as a linear mapping on a properly defined functional spaces, have become key problems in nonlinear system identification and control.
Wentao Tang
semanticscholar +1 more source
Theoretical properties and data-driven learning of the Koopman operator, which represents nonlinear dynamics as a linear mapping on a properly defined functional spaces, have become key problems in nonlinear system identification and control.
Wentao Tang
semanticscholar +1 more source
Conference on Robot Learning
Developing agents that can perform complex control tasks from high-dimensional observations is a core ability of autonomous agents that requires underlying robust task control policies and adapting the underlying visual representations to the task.
Hemant Kumawat +2 more
semanticscholar +1 more source
Developing agents that can perform complex control tasks from high-dimensional observations is a core ability of autonomous agents that requires underlying robust task control policies and adapting the underlying visual representations to the task.
Hemant Kumawat +2 more
semanticscholar +1 more source
Koopman Operator-based Model Identification and Control for Automated Driving Vehicle
International Journal of Control, Automation and Systems, 2023Jin Sung Kim, Y. Quan, C. Chung
semanticscholar +1 more source
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators
Nature Machine Intelligence, 2021Lu Lu, Pengzhan Jin, Guofei Pang
exaly