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.