37 citations · 41 across the 5 of their papers we have counts for
5 papers
Reinforcement Learning-based Output Structured Feedback for Distributed Multi-Area Power System Frequency Control
Kyung-bin Kwon, Sayak Mukherjee, Hao Zhu +1
Load frequency control (LFC) is a key factor to maintain the stable frequency in multi-area power systems. As the modern power systems evolve from centralized to distributed paradi…
Model-free Learning for Risk-constrained Linear Quadratic Regulator with Structured Feedback in Networked Systems
Kyung-bin Kwon, Lintao Ye, Vijay Gupta +1
We develop a model-free learning algorithm for the infinite-horizon linear quadratic regulator (LQR) problem. Specifically, (risk) constraints and structured feedback are considere…
On the Sample Complexity of Decentralized Linear Quadratic Regulator with Partially Nested Information Structure
Lintao Ye, Hao Zhu, Vijay Gupta
We study the problem of control policy design for decentralized state-feedback linear quadratic control with a partially nested information structure, when the system model is unkn…
Achieving Optimal Output Consensus for Discrete-time Linear Multi-agent Systems with Disturbance Rejection
Yutao Tang, Hao Zhu, Xiaoyong Lv
In this paper, an optimal output consensus problem is studied for discrete-time linear multiagent systems subject to external disturbances. Each agent is assigned with a local cost…
Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies
Kaiqing Zhang, Alec Koppel, Hao Zhu +1
Policy gradient (PG) methods are a widely used reinforcement learning methodology in many applications such as video games, autonomous driving, and robotics. In spite of its empiri…