Adaptive PID controller based on Q ‐learning algorithm-Reference-Cited by-同舟云学术

Adaptive PID controller based on Q ‐learning algorithm

Published:2018-11-14 Issue:4 Volume:3 Page:235-244
ISSN:2468-2322
Container-title:CAAI Transactions on Intelligence Technology
language:en
Short-container-title:CAAI Transactions on Intelligence Technology

Author:

Shi Qian¹,Lam Hak‐Keung¹,Xiao Bo²,Tsai Shun‐Hung³

Affiliation:

1. Department of InformaticsKing's College LondonBush House, Strand Campus, 30 AldwychLondonWC2B 4BGUK

2. Hamlyn Centre for Robotic Surgery, Imperial College LondonLondonSW7 2AZUK

3. Graduate Institute of Automation Technology, National Taipei University of TechnologyTaipei10608Taiwan

Funder

Ministry of Science and Technology, Taiwan

Publisher

Institution of Engineering and Technology (IET)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Vision and Pattern Recognition,Human-Computer Interaction,Information Systems

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/trit.2018.1007

Reference25 articles.

1. MirandaM.F.VamvoudakisK.G.: ‘Online optimal auto‐tuning of PID controllers for tracking in a special class of linear systems’.American Control Conf. (ACC) Boston MA 2016 pp.5443–5448

2. Incremental Q -learning strategy for adaptive PID control of mobile robots

3. ShadiM.SargolzaeiM.: ‘Application of reinforcement learning to improve control performance of plant’.IEEE Int. Conf. Computational Intelligence for Measurement Systems and Applications Istanbul 2008

4. LillicrapT.P.HuntJ.J.PritzelA.et al.: ‘Continuous control with deep reinforcement learning’ arXiv preprint arXiv:1509.02971 2015

5. BagnellJ.A.SchneiderJ.G.: ‘Autonomous helicopter control using reinforcement learning policy search methods’.Proc. IEEE Int. Conf. on Robotics and Automation Seoul South Korea 2001 vol.2 pp.1615–1620

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