Work

Reinforcement Learning-Based H∞ Control of 2-D Markov Jump Roesser Systems With Optimal Disturbance Attenuation

Year: 2024

Type: article

Source: IEEE Transactions on Neural Networks and Learning Systems

DOI: 10.1109/tnnls.2024.3487760

Authors: Jiacheng Wu, Bosen Lian, Hongye Su, Yang Zhu

Institutions: State Key Laboratory of Industrial Control Technology, Zhejiang University, Auburn University

Language: English

Topic: Adaptive Dynamic Programming Control

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funder: National Natural Science Foundation of China

Awards: G2335503236, G987444751

OpenAlex ID: W4404101325

FWCI: 1.2

Cites: 41

Cited by: 6

Related to: 10