6 citations · 14 across the 6 of their papers we have counts for
6 papers
Model-free Nearly Optimal Control of Constrained-Input Nonlinear Systems Based on Synchronous Reinforcement Learning
Han Zhao, Lei Guo
In this paper a novel model-free algorithm is proposed. This algorithm can learn the nearly optimal control law of constrained-input systems from online data without requiring any…
A Nearly Optimal Chattering Reduction Method of Sliding Mode Control With an Application to a Two-wheeled Mobile Robot
Lei Guo, Han Zhao, Yuan Song
The problem we focus on in this paper is to find a nearly optimal sliding mode controller of continuous-time nonlinear multiple-input multiple-output (MIMO) systems that can both r…
Online Continual Adaptation with Active Self-Training
Shiji Zhou, Han Zhao, Shanghang Zhang +4
Models trained with offline data often suffer from continual distribution shifts and expensive labeling in changing environments. This calls for a new online learning paradigm wher…
Online Adaptive Optimal Control Algorithm Based on Synchronous Integral Reinforcement Learning With Explorations
Lei Guo, Han Zhao
In this paper, we present a novel algorithm named synchronous integral Q-learning, which is based on synchronous policy iteration, to solve the continuous-time infinite horizon opt…
Adaptive Fractional-Order Sliding Mode Controller with Neural Network Compensator for an Ultrasonic Motor
Xiaolong Chen, Wenyu Liang, Han Zhao +1
Ultrasonic motors (USMs) are commonly used in aerospace, robotics, and medical devices, where fast and precise motion is needed. Remarkably, sliding mode controller (SMC) is an eff…
Model-based Policy Optimization with Unsupervised Model Adaptation
Jian Shen, Han Zhao, Weinan Zhang +1
Model-based reinforcement learning methods learn a dynamics model with real data sampled from the environment and leverage it to generate simulated data to derive an agent. However…