GOPS: A general optimal control problem solver for autonomous driving and industrial control applications

GOPS: A general optimal control problem solver for autonomous driving and industrial control applications

Solving optimal control problems serves as the basic demand of industrial control tasks. Existing methods like model predictive control often suffer from heavy online computational burdens. Reinforcement learning has shown promise in computer and board games but has yet to be widely adopted in indus...

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Bibliographic Details
Main Authors: Wenxuan Wang, Yuhang Zhang, Jiaxin Gao, Yuxuan Jiang, Yujie Yang, Zhilong Zheng, Wenjun Zou, Jie Li, Congsheng Zhang, Wenhan Cao, Genjin Xie, Jingliang Duan, Shengbo Eben Li
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Communications in Transportation Research
Subjects:
Industrial control
Reinforcement learning
Approximate dynamic programming
Optimal control
Neural network
Benchmark
Online Access:http://www.sciencedirect.com/science/article/pii/S2772424723000070

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http://www.sciencedirect.com/science/article/pii/S2772424723000070

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