城市污水处理过程动态多目标智能优化控制研究

城市污水处理过程(Municipal wastewater treatment process, MWWTP)是一个典型的复杂流程工业过程, 其优化运行涉及到多个动态性能指标. 为了实现城市污水处理运行过程的优化控制, 本文提出了一种城市污水处理过程动态多目标智能优化控制方法(Dynamic multiobjective intelligent optimal control, DMIOC). 首先, 建立了一种基于自适应核函数的动态性能指标模型, 实现了城市污水处理关键性能指标的准确描述; 其次, 设计了一种基于自适应飞行参数调整机制的动态多目标粒子群优化算法(Dynamic multiobjective particle swarm optimization, DMOPSO), 可有效平衡粒子的多样性和收敛性, 完成了溶解氧和硝态氮优化设定值的实时获取; 最后, 利用多回路PID控制方法对溶解氧和硝态氮优化设定值进行控制, 实现了城市污水处理过程安全稳定运行. 将提出的DMIOC应用于城市污水处理基准仿真平台, 实验结果显示: DMIOC 能够提高溶解氧和硝态氮的控制效果, 实现城市污水处理过程出水水质达标, 并降低运行成本.

Research on Dynamic Multiobjective Intelligent Optimal Control for Municipal Wastewater Treatment Process

Municipal wastewater treatment process(MWWTP)is a typical complex industrial process,where multiple dynamic performance indices are contained in the optimal operational process.To realize the optimal operational control of MWWTP,a dynamic multiobjective intelligent optimal control(DMIOC)strategy is proposed in this paper.First,dynamic performance index model based on adaptive kernel function was established.Then the dynamic characteristics of performance indices could be accurately captured.Second,a dynamic multiobjective particle swarm optimization(DMOPSO)algorithm,based on an adaptive flight parameter adjustment mechanism,was designed.It can efficiently balance the diversity and convergence of the particles.Then the real-time optimal setpoints of the control variables dissolved oxygen and nitrate nitrogen could be obtained.Third,a multi-loop PID control strategy was utilized to realize the control of the optimal set-points of dissolved oxygen and nitrate nitrogen.The proposed DMIOC strategy was tested in the benchmark simulation model to evaluate its effectiveness.The results demonstrate that the proposed DMIOC strategy can realize the dynamic optimal control of the control variables dissolved oxygen and nitrate nitrogen,guarantee the effluent qualities in the limits and reduce the operation cost.