Model-free MIMO control tuning of a chiller process using reinforcement learning-Reference-Cited by-同舟云学术

Model-free MIMO control tuning of a chiller process using reinforcement learning

Published:2023-09-04 Issue:8 Volume:29 Page:782-794
ISSN:2374-4731
Container-title:Science and Technology for the Built Environment
language:en
Short-container-title:Science and Technology for the Built Environment

Author:

Rosdahl Christian¹^ORCID,Bernhardsson Bo¹^ORCID,Eisenhower Bryan²^ORCID

Affiliation:

1. Department of Automatic Control, Lund University, Lund, Sweden

2. Carrier World Headquarters, Palm Beach Gardens, Florida, USA

Publisher

Informa UK Limited

Subject

Fluid Flow and Transfer Processes,Building and Construction,Environmental Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/23744731.2023.2247938

Reference34 articles.

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2. Anderson M. P. Young D. Hittle C. Anderson J. Tu and D. Hodgson. 2002. MIMO robust control for heating ventilating and air conditioning (HVAC) systems. In Proceedings of the 41st IEEE Conference on Decision and Control 167–72.

3. Design of Self-Tuning SISO Partial-Form Model-Free Adaptive Controller for Vapor-Compression Refrigeration System

4. Inverse reinforcement learning control for building energy management

5. Duan Y. X. Chen R. Houthooft J. Schulman and P. Abbeel. 2016. Benchmarking deep reinforcement learning for continuous control. In International conference on machine learning PMLR 1329–1338.

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