Kazushi Tsumura

SYSTEM IDENTIFICATION AND CONTROL OF ACTIVATED SLUDGE PROCESS BY USE OF AUTOREGRESSIVE MODEL

ABSTRACT He experimented the system identification and control of an activated sludge process by using an autoregressive model in an real wastewater treatment plant. The control system used in this experiment was a cooperative type based on a combination of conventional PI control and autoregressive model. In system identification, we constructed an autoregressive model from the process data that was obtained by changing manipulated variables such as return sludge flow rate, excess sludge flow rate, and air flow rate in terms of noise. We confirmed the validity of this model from its analytical results, and observed through control simulation that the model could dynamically control treated sewage quality. Next, by using this model and optimum feedback gain, we experimented control performance to check treated sewage quality for approximately one month in a real wastewater treatment plant. As a result, we confirmed that control by the autoregressive model operates exactly the way we initially anticipated. Thus, it was clarified that cooperative-type control systems are effective for suppressing fluctuations in treated sewage quality.

AUTOMATIC MEASUREMENT AND ANALYSIS OF PROCESS DATA IN A COMBINED WASTEWATER TREATMENT PLANT

ABSTRACT For automatic control, even for manual control, the reliability of measurements is a prior condition. The authors installed automatic measuring instruments in a combined wastewater treatment plant which treated 80,000 m 3 sewage per day and gathered data every fifteen minutes for a year. In this paper the results from these experiments are presented. Measured items and their sampling points were flow rate, UV, SS, pH at the outlet of the primary settling tank, air flow rate, MLSS, temperature, three DO concentrations along the flow in the aeration tank, flow rate and SS of the return and excess sludge and rainfall intensity. The discussions in this paper are as follows, (1) verification of instruments, (2) data collection and pretreatment and (3) analysis of data.

Control of dioxins from municipal solid waste incinerator

Abstract The purpose of this study is to establish whether intermediate products, which are remained as unburned components and become the precursors to form the PCDD, can be reduced by improvement of the plant operation. The change of the PCDD levels was analyzed along the stream of the flue gas. Two test programs were conducted to reduce the emission levels of PCDD at municipal solid waste (MSW) incinerators. They were as follows; 1. (1) High temperature incineration to reduce unburned components. 2. (2) Investigation of the relationship between CO contents and PCDD levels at an incinerator which was operated by reductive two-step combustion mode to reduce NOx emission level.

STATISTICAL ANALYSIS OF ACTIVATED SLUDGE PROCESS DYNAMICS IN A COMBINED WASTEWATER TREATMENT PLANT

ABSTRACT On the basis of the results of analyzing the dynamic behavior of an activated sludge process, the authors have considered that its control systems must be constructed hierarchically and concluded that a statistical model is suitable for expressing short-time variation. In this paper, the results of applying an AR model (which belong to the statistical models) to an activated sludge process of a combined wastewater treatment plant are presented. First, by a one point prediction and the response of system variables using white noise, the fabricated AR model was tested. Next, the effects of its own noise on the variables of the system to the variation of controlled variables were calculated by using this model. As a result, it was judged that the model was adequate, and fully expressed the dynamics of the process objectives.

Computer-based filamentous microorganism identification support system

A computer-based filamentous microorganism identification support system was developed to assist field operators who encounter the bulking problem in a waste water treatment plant using the activated sludge process. An image processing system monitors the amount of the filamentous bacteria. If anything unusual happens, the filamentous/microorganism identification support system starts. The system leads an operator toward its user model, and identifies the type of the predominant filamentous bacteria. Based on the result of identification, a control is carried out and the effect of this control action is monitored by the identification support system. If the bulking is suppressed, the support system stops. Hardware and software features of the system are described.<<ETX>>

Modeling and Control of the Activated Sludge Process by Use of Autoregressive Model

Abstract The authors have insisted that the control systems must be constructed hierarchically. In the bottom level of this system, the statistical model is suitable to express the dynamics of the activated sludge process. In this paper, it is shown that an AR model which belongs to the statistical model is applicable to the activated sludge process in the combined wastewater treatment plant. Next, it is discussed how to change the manipulated variables on purpose to clearly determine the effects of the manipulated variables, because the manipulated variables are generally maintained almost constant in the actual plants.