32 citations · 35 across the 17 of their papers we have counts for
4 papers · 1 filter
Robust Bayesian Inference for Moving Horizon Estimation
Wenhan Cao, Chang Liu, Zhiqian Lan +3
The accuracy of moving horizon estimation (MHE) suffers significantly in the presence of measurement outliers. Existing methods address this issue by treating measurements leading…
On the Optimization Landscape of Dynamic Output Feedback: A Case Study for Linear Quadratic Regulator
Jingliang Duan, Wenhan Cao, Yang Zheng +1
The convergence of policy gradient algorithms in reinforcement learning hinges on the optimization landscape of the underlying optimal control problem. Theoretical insights into th…
Primal-dual Estimator Learning: an Offline Constrained Moving Horizon Estimation Method with Feasibility and Near-optimality Guarantees
Wenhan Cao, Jingliang Duan, Shengbo Eben Li +3
This paper proposes a primal-dual framework to learn a stable estimator for linear constrained estimation problems leveraging the moving horizon approach. To avoid the online compu…
On the Optimization Landscape of Dynamic Output Feedback Linear Quadratic Control
Jingliang Duan, Wenhan Cao, Yang Zheng +1
The convergence of policy gradient algorithms hinges on the optimization landscape of the underlying optimal control problem. Theoretical insights into these algorithms can often b…