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Soft Sensor and Adaptive Model-Based Dissolved Oxygen Control for Biological Wastewater Treatment Processes

机译：软传感器和基于自适应模型的生物废水溶解氧控制

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摘要

In wastewater treatment processes (WWTP), the respiration rate (R) and oxygen transfer rate (K_La) are two of the most important variables for monitoring biological activity and assessing process control performance. Knowledge of the two variables is therefore of interest in both process diagnosis and process control. In consideration of the combined mechanism of dissolved oxygen (DO) control and R/K_La estimation, we used a generalized damped least squares (GDLS) method as a soft sensor of the two key variables under closed loop control. The estimated values of the two key variables were then used to derive an adaptive model-based DO control law using the soft sensing ability of the GDLS. Simulation results show that the GDLS algorithm gives excellent estimations of the respiration rate under closed loop control, and that model-based DO control can efficiently deal with changes in the operating condition.
机译：在废水处理过程（WWTP）中，呼吸速率（R）和氧转移速率（K_La）是监测生物活性和评估过程控制性能的两个最重要变量。因此，在过程诊断和过程控制中都需要了解这两个变量。考虑到溶解氧（DO）控制和R / K_La估计的组合机制，我们使用广义阻尼最小二乘（GDLS）方法作为闭环控制下两个关键变量的软传感器。然后，使用GDLS的软传感能力，将两个关键变量的估计值用于得出基于自适应模型的DO控制律。仿真结果表明，GDLS算法可以很好地估计闭环控制下的呼吸速率，并且基于模型的DO控制可以有效地应对运行条件的变化。

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