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Data-knowledge driven optimal control method for municipal wastewater treatment process
Data-knowledge driven optimal control method for municipal wastewater treatment process
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机译：数据知识驱动的市政污水处理过程最优控制方法
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摘要
A data-knowledge driven multi-objective optimal control method for municipal wastewater treatment process belongs to the field of wastewater treatment. To balance the energy consumption and effluent quality, a data driven multi-objective optimization model, including energy consumption model and effluent quality model are established to obtain the nonlinear relationship along energy consumption, effluent quality and manipulated variables. Meanwhile, a multi-objective particle swarm optimization algorithm, based on evolutionary knowledge, is proposed to optimize the set-points of nitrate nitrogen and dissolved oxygen. Moreover, the proportional integral differential (PID) controller is designed to track the set-points. Then the effluent quality can be improved and the energy consumption can be reduced.
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