QIN Bin, WU Min, WANG Xin, et al. Multi-Level Coordination Control Based on Multi-Agent Reinforcement Learning for the Pressure of Gas Collectors of Coke Ovens[J]. Acta Electronica Sinica, 2006, 34(10): 1847-1851.
DOI:
QIN Bin, WU Min, WANG Xin, et al. Multi-Level Coordination Control Based on Multi-Agent Reinforcement Learning for the Pressure of Gas Collectors of Coke Ovens[J]. Acta Electronica Sinica, 2006, 34(10): 1847-1851.DOI:
Multi-Level Coordination Control Based on Multi-Agent Reinforcement Learning for the Pressure of Gas Collectors of Coke Ovens
For the multi-variable nonlinear coupled system with strong disturbance such as the gas pressure of collectors of coke ovens
this paper proposes an intelligent multi-level coordinated control strategy based on multi-agent system.It adopts the multi-level coordination architecture with agent agency and the organization and evolution mechanism based on task decomposition.The system can be switched to different modes using the state change of agents in order to operate in rapidly time-varying environments.The reinforcement learning method is used in Agent learning
the TS type recurrent fuzzy neural network(TSRFNN) is employed to realize the actor-critic elements.The agents in system are optimized coordinately by using the distributed learning algorithm.The real-world application shows that the proposed control strategy has successfully solved the process coordination control problem of the gas pressure of collectors of coke ovens with the strong disturbance produced by high pressure ammonia.