This paper presents a real-time optimal control scheme based on a total cost index (TCI) by using the so-called extremum seeking control (ESC). The ESC searches the minimum value of a given performance index where the TCI consisting of the operational cost and the effluent quality cost is used as the index. An improved ESC is proposed where a transformed TCI by monotonically increasing function is utilized to improve the convergence property of the ESC while keeping the argument of the optimal point invariant. The feasibility of the ESC is tested for two types of pseudo-anaerobic-oxic process control: one is the return sludge recycle ratio control, and the other is the aeration control for an alternate zone which can be anaerobic or aerobic depending on the influent condition. Simulation study illustrates that the proposed ESC is able to find a near optimal point successfully and the TCI can be reduced by about 2.7 to 3.8% compared with that of a typical operating condition.
This paper presents a new knowledge discovery assistance method to improve wastewater treatment plant (WWTP) operation based on multivariate statistical process control (MSPC). The proposed method combines with MSPC by principal component analysis (PCA-MSPC) and monitoring of a pre-defined performance index for efficient and stable plant operation. Fault detection and isolation (FDI) related to the performance index is selectively performed by monitoring the time series data of the performance index wherein the sample points violating the control limit of Q statistic or that of T 2 statistic in PCA-MSPC are indicated. Hidden patterns of probable cause variables to deteriorate the performance index are discovered from the FDI by observing the time series data of the isolated variables. Applications of the proposed method to real WWTPs illustrate the effectiveness of the proposed method by showing possible improvement for energy-saving operation and stable plant operation.Keywords: multivariate statistical process control, stable and energy saving process operation, wastewater treatment
INTRODUCTIONEfficient plant operation of wastewater treatment plants (WWTPs) is becoming increasingly important due to the requirement of the effective use of budget in many municipalities and due to the decrease of skilled plant operators as a result of an aging population. For efficient operation, it is of course important that the number of WWTP operators should be minimized as much as possible. Another view of efficient plant operation is energy saving operation. Social requirement for CO 2 reduction is certainly a driving force to improve the efficiency of daily plant operation. To achieve such an efficient plant operation, it is promising to utilize massive amounts of time series process data acquired by supervisory control and data acquisition (SCADA) system that is often installed for process monitoring and operation. In SCADA system, process data are often used only for such monitoring and operation purposes. However, process data can be more effectively used to support decision making for the improvement of plant operation since process measurement signals are often highly interrelated and usually represent the cumulative effects of many underlying process phenomena such as process dynamics, external disturbances and process degradation among others. In addition, rapid development of information technology (IT) helped to increase the number of available online data and thus, useful information involved in process data are potentially increasing. However, such data have not often been used effectively to
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.