Q-Learning Based Parameter Tuning for Model-free Adaptive Control of Nonlinear Systems

被引：0

作者：

Xu, Liuyong ^{[1
]}

Hao, Shoulin ^{[1
]}

Liu, Tao ^{[1
]}

Zhu, Yong ^{[1
]}

Wang, Haixia ^{[1
]}

Zhang, Jiyan ^{[1
]}

机构：

[1] Dalian Univ Technol, Key Lab Intelligent Control & Optimizat Ind Equip, Minist Educ, Dalian, Peoples R China

来源：

2024 14TH ASIAN CONTROL CONFERENCE, ASCC 2024 | 2024年

关键词：

Nonlinear systems; model-free adaptive control; Q-learning; reinforcement learning; parameter optimization;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a Q-learning based parameter tuning method is proposed for the model-free adaptive control (MFAC) of nonlinear systems with unknown dynamics. Based on the partitioned state and action spaces, a novel reward function is firstly introduced to establish a Q-table offline training algorithm. Then, an online parameter optimization procedure is developed by means of the established Q-table, so as to enhance the learning ability and adaptability of the control system. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method in comparison with the existing parameter tuning methods of MFAC.

引用

页码：2078 / 2083

页数：6

共 19 条

[1] Using Q-learning to Automatically Tune Quadcopter PID Controller Online for Fast Altitude Stabilization
Alrubyli, Yazeed
Bonarini, Andrea
[J]. PROCEEDINGS OF 2022 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (IEEE ICMA 2022), 2022, : 514 - 519
[2] Astrom K. J., RES TRIANGLE PARK
[3] Q-Learning-based parameters adaptive algorithm for active disturbance rejection control and its application to ship course control
Chen, Zengqiang
Qin, Beibei
Sun, Mingwei
Sun, Qinglin
[J]. NEUROCOMPUTING, 2020, 408 : 51 - 63
[4] Model-free adaptive control optimization using a chaotic particle swarm approach
Coelho, Leandro dos Santos
Rodrigues Coelho, Antonio Augusto
[J]. CHAOS SOLITONS & FRACTALS, 2009, 41 (04) : 2001 - 2009
[5] Feng Z., 2021, COMPUTER SIMULATION, V38, P170
[6] [冯增喜 Feng Zengxi], 2021, [控制工程, Control Engineering of China], V28, P766
[7] Hou Z., 2013, Model Free Adaptive Control: Theory and Applications
[8] HOU ZS, 2013, SURVEY, V235, P3, DOI DOI 10.1016/J.INS.2012.07.014
[9] Review of reinforcement learning research
Jia, Jingkai
Wang, Wenlin
[J]. 2020 35TH YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC), 2020, : 186 - 191
[10] Parameter tuning of the PG initial values for direct model-free adaptive control based on PID tuning methods
Li X.
Hou Z.-S.
[J]. Kongzhi Lilun Yu Yingyong/Control Theory and Applications, 2023, 40 (10): : 1737 - 1745

← 1 2 →