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eess.SY2025
Differentiable Physics-Informed Adaptive Koopman Control for Stable Flight under Unknown Disturbances
Ao Jin, Qiujin Liang, Tao Zhang +2
Uncertainties and disturbances in robotic systems, such as aerodynamic forces, are fundamentally outcomes of physical interactions with the environment, manifesting as learnable sp…
eess.SY2025
Enhanced Robust Tracking Control: An Online Learning Approach
Ao Jin, Weijian Zhao, Yifeng Ma +2
This work focuses the tracking control problem for nonlinear systems subjected to unknown external disturbances. Inspired by contraction theory, a neural network-dirven CCM synthes…
eess.SY2023★ 11 cited
Data-Driven Optimal Control of Tethered Space Robot Deployment with Learning Based Koopman Operator
Ao Jin, Fan Zhang, Panfeng Huang
To avoid complex constraints of the traditional nonlinear method for tethered space robot (TSR) deployment, this paper proposes a data-driven optimal control framework with an impr…