首页|Reinforcement Learning in Process Industries:Review and Perspective
Reinforcement Learning in Process Industries:Review and Perspective
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This survey paper provides a review and perspec-tive on intermediate and advanced reinforcement learning(RL)techniques in process industries.It offers a holistic approach by covering all levels of the process control hierarchy.The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL,such as value-based,policy-based,and actor-critic methods,while also discussing the rela-tionship between classical control and RL.It further reviews the wide-ranging applications of RL in process industries,such as soft sensors,low-level control,high-level control,distributed process control,fault detection and fault tolerant control,optimization,planning,scheduling,and supply chain.The survey paper dis-cusses the limitations and advantages,trends and new applica-tions,and opportunities and future prospects for RL in process industries.Moreover,it highlights the need for a holistic approach in complex systems due to the growing importance of digitaliza-tion in the process industries.
Process controlprocess systems engineeringrein-forcement learning
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维普
