3 papers
eess.SY2025
Sparse Kalman Identification for Partially Observable Systems via Adaptive Bayesian Learning
Jilan Mei, Tengjie Zheng, Lin Cheng +2
Sparse dynamics identification is an essential tool for discovering interpretable physical models and enabling efficient control in engineering systems. However, existing methods r…
cs.LG2025
Recursive Gaussian Process State Space Model
Tengjie Zheng, Haipeng Chen, Lin Cheng +2
Learning dynamical models from data is not only fundamental but also holds great promise for advancing principle discovery, time-series prediction, and controller design. Among var…
eess.SY2025
Learning-Based Stable Optimal Control for Infinite-Time Nonlinear Regulation Problems
Han Wang, Di Wu, Lin Cheng +2
Infinite-time nonlinear optimal regulation control is widely utilized in aerospace engineering as a systematic method for synthesizing stable controllers. However, conventional met…