Abstract: The distribution and supply of aeration in most domestic wastewater treatment plants are unsatisfactory, resulting in delayed, low-precision, and highly volatile dissolved oxygen concentration control, leading to high energy consumption and directly impacting treatment efficiency. This paper describes a successfully developed and applied intelligent control system for aeration in the biological treatment tanks of wastewater treatment plants. This system, employing cascade, feedforward, and feedback control and intelligent models, ensures aeration balance under both constant and changing water quality and quantity conditions. Furthermore, it adjusts the blower's operating pressure based on valve opening to achieve energy savings. This paper focuses on the design concept, system configuration, control algorithm, and software design of the control system, and presents its practical application results. Keywords: aeration volume, dissolved oxygen concentration control, intelligent control PLC Abstract: In view of the existing problem of the majority domestic wastewater treatment plant, such as the aeration quantity assignment and the effect of supply are not very ideal, the lag controlling of the dissolved oxygen concentration ,and its low precision, big fluctuations, high energy consumption ,which directly influence the processing effect. This paper describes the succeeded developed and used intelligent system which controls the aeration quantity of the wastewater treatment biochemistry tank. This system will use the series, the forward feed, the feedback control and the intelligence model to guarantee the balance of aeration whether the quality and quantity of the water change or not. At the same time, according to the opening size of the valve, it will adjust the service pressure of the air blower for the sake of saving energy. This paper emphasizes the introduction of the design idea, the configuration, the arithmetic, the software design of the control system. In the mean while, the actual use effect is given. Key words: Aeration Quantity; Dissolved Oxygen concentration Control; PLC; Intelligence control 1. Introduction Currently, wastewater treatment processes both domestically and internationally mainly employ traditional activated sludge processes and their variations: AB process, AO process, A2O process (and its improvements), SBR process, CASS, etc. Among these, controlling the aeration rate in the biological treatment tank remains a persistent challenge. The distribution of dissolved oxygen during aeration directly affects the wastewater treatment effect, sludge activity, and even effluent quality. In Europe, the setpoint for dissolved oxygen concentration has decreased from 2-5 mg/L ten years ago to 2 mg/L in the last ten years, and now to 1.0-1.2 mg/L. Internationally, efforts are being made to continuously refine the optimal dissolved oxygen concentration based on different operational conditions, lowering the original setpoint. Currently, the distribution and supply of aeration in most domestic wastewater treatment plants is far from ideal, with large fluctuations in dissolved oxygen concentration and significant differences between the surrounding and upstream sections, directly impacting effluent quality. Most wastewater treatment plants still rely on remote manual control for aeration distribution and supply, which is prone to errors and can cause human-induced stress on the system. Some wastewater treatment plants also use automated control systems, which employ a method of controlling the treatment process using dissolved oxygen signals from the biological treatment tank as control signals and butterfly valves as actuators to regulate the dissolved oxygen concentration in the aeration tank at setpoints. However, in actual operation and control of wastewater treatment plants, neither of these methods achieves satisfactory control results, exhibiting issues such as control lag, low precision, large fluctuations in dissolved oxygen levels, high energy consumption, and a direct impact on treatment effectiveness. Therefore, it is necessary to research and promote new control systems to improve the production process level of urban sewage treatment, and these systems should meet the following requirements: Precise and stable control of dissolved oxygen concentration in the sewage aeration tank to improve the biochemical treatment rate and effluent quality; Real-time adjustment of dissolved oxygen concentration and gas flow rate based on wind direction, wind force, temperature, and influent water quality to ensure timely, accurate, and scientific gas distribution; Optimization of blower operation to achieve energy saving and consumption reduction; Avoidance of process paralysis due to dissolved oxygen meter malfunction, and prevention of microbial growth and survival rates caused by insufficient or excessive aeration, thus affecting the normal production of the sewage treatment plant; Reduction of sewage treatment plant operating costs, reduction of operational difficulty for on-duty personnel, and improvement of work efficiency; Replacement of similar foreign products, generating foreign exchange through exports. 2. Design Philosophy Under stable system conditions, assuming that influent flow rate, water quality, water temperature, etc., remain constant, blower outlet pressure and aeration rate remain constant, oxygen consumption rate and oxygenation rate are basically balanced, and dissolved oxygen concentration remains stable at a given value. However, it's impossible for the wastewater treatment process to maintain such an ideal balance forever. Disturbances will inevitably disrupt this balance, so advanced automatic adjustment methods are necessary to ensure the system can quickly return to stability. When water quality and quantity remain constant, how can the system maintain aeration balance? If the influent water quality and quantity are relatively stable, changes in the blower's outlet pressure or flow rate due to external factors, or variations in the aeration rate of other local control loops, will disrupt the balance. Each field control loop in the control system is equipped with a high-precision gas flow meter that continuously and accurately measures changes in gas flow. When a disturbance occurs, the flow meter in that loop immediately detects the change and promptly relays it to the loop's input. The flow control loop quickly assesses this change and rapidly adjusts the opening of the high-precision regulating valve in that loop to maintain a constant aeration rate. In this way, through the control of the flow control loop, the interference is overcome before it affects dissolved oxygen. Even if the interference is large, most of its impact has been overcome by the flow control loop. By the time it affects dissolved oxygen, the interference is already very small. Further adjustment by the flow calculation loop completely eliminates the interference, restoring dissolved oxygen to the set value. When water quality and quantity change, how does the system ensure aeration? If the air supply system is stable, but the water quality and quantity entering the aeration tank change, causing fluctuations in dissolved oxygen and disrupting the original balance, the control system includes a flow calculation unit and a flow control unit. When an interference occurs, the flow meter reflects the actual measured gas flow rate to the flow calculation unit. The set value of dissolved oxygen, the actual measured value of dissolved oxygen, the trend of dissolved oxygen change, and ammonia nitrogen signals are also simultaneously reflected to the flow calculation unit. Combining historical data with the system's fuzzy control program, the system will reset the gas flow set value according to actual needs and reflect it to the flow control unit, promptly adjusting the aeration rate of the field loop. The interference is overcome, and dissolved oxygen quickly returns to the set value. How to intelligently control the operating pressure of the blower to achieve energy saving? Aeration power consumption accounts for about 80% of the wastewater treatment plant's total power consumption. Therefore, it is essential to reduce energy consumption through advanced control algorithms. If the current operating pressure of the blower is relatively high, and the valve openings are relatively small, the system is in a relatively energy-intensive state. Therefore, the pressure control unit in the control system integrates all actual gas flow signals and valve position signals, calculates and provides a minimum required pressure setting, and readjusts the blower's operating pressure (adjusting the inlet guide vanes or frequency converter) to achieve the purpose of supplying gas according to actual needs. 3. System Implementation [align=center] Figure 1 System Control Loop Diagram[/align] 3.1 System Configuration The system control components are shown in Figure 1. The system uses a thermally effective gas mass flow meter as the main sensor. Compared with a DO meter, its measurement data is more accurate and requires virtually no maintenance. The thermally effective gas mass flow meter adopts the principle of thermal diffusion, a technology with excellent performance and high reliability under harsh conditions. The system uses a diamond-shaped regulating valve to replace the butterfly valve in the traditional control. The rhomboid regulating valve has two advantages: first, it exhibits a linear relationship within the 0-100% adjustment range, possessing an equal percentage flow characteristic, while the butterfly valve only exhibits a linear relationship within the 25-65% range; second, this type of valve has a smaller step value, thus allowing for precise adjustment of the air supply. [align=center]Figure 2 Control Configuration Diagram[/align] The system controller uses a Modicon series PLC from the French company Schneider, and the control configuration is shown in Figure 2. Considering that one blower drives four aeration circuits, an 8-channel input analog module and a 4-channel output analog module are selected to form a control closed loop. The PLC is integrated into the factory control network and communicates with the plant-level control system (including blower control, water quality monitoring, etc.) via the MODBUS PLUS network. A 10.4-inch 64-color touchscreen from Schneider is selected as the human-machine interface. 3.2 Control Algorithm Based on the design concept described above, the system adopts a cascade PID control system: the dissolved oxygen concentration in the main loop is adjusted by setting the aeration rate, employing a complex control combining feedforward and feedback. The disturbance variable for feedforward control is taken as water quality (ammonia nitrogen, nitrate nitrogen, etc.). Based on changes in water quality, the setpoint for dissolved oxygen, the current dissolved oxygen value, and historical data over a certain period, a new setpoint for aeration rate is calculated and assigned. The aeration rate in the secondary loop is adjusted by the valve opening, also employing a complex control combining feedforward and feedback. The disturbance variable for feedforward control is taken as the setpoint for the total outlet pressure of the blower. This quickly overcomes interference caused by changes in the setpoint for the total outlet pressure of the blower control system, while feedback control can quickly adjust the valve opening according to the aeration rate, simultaneously overcoming interference caused by different pipelines sharing a single blower. The cascade control system has the advantages of anti-interference, speed, adaptability, and good control quality. If the openings of all four valves are relatively small, the pipeline resistance is relatively high, leading to increased blower energy consumption and decreased efficiency. Therefore, the opening of all four valves can be increased appropriately while the total outlet pressure setpoint of the blower control system is reduced, thus achieving energy saving. The change in aeration volume caused by the change in the total outlet pressure of the blower can be quickly eliminated by the feedforward circuit. The valve opening should not be increased too much, otherwise there will be little room for adjustment. 3.3 Software Design The programming software of the Modicon Quantum series PLC provides a rich function library, making it more powerful in process control. The following is a brief introduction to several main control functions used in the software programming: SAMPLETM, PIDFF, and MS. The SAMPLETM function is used for timing, and the INTERVAL pin is used to specify the time interval; the PIDFF function is a PID controller with a feedforward input pin FF, which is very powerful, supporting incremental and absolute PID calculations, output signal amplitude and gradient limiting, automatic/manual switching, and the Para_PIDFF pin is the PID parameter data block; MS is the output control function, and the value of its OUT pin can be the output value of the PID calculation or the operation value on the human-machine interface, set through the MAN_AUTO pin to achieve seamless automatic/manual bidirectional switching. The cascaded PID control algorithm described above is conveniently implemented by connecting the three functions in two sets. [align=center]Figure 3 Several main process control functions[/align] The touch screen software is written using Vijeo-Designer configuration software. The monitoring system running on the touch screen has two working modes: master automatic and master manual. Master automatic refers to control by the PLC's internal algorithm, and the control mode can be switched to manual, directly setting the valve opening on the touch screen. The touch screen can display the process flow and measurement parameters, control mode, program running status, controlled object status, historical curves, and can also display group parameters. When parameters exceed limits, alarms are triggered, controlled objects malfunction, or status changes occur, different colors can be used to display them. 4. Conclusion This system has been successfully applied, accurately controlling the dissolved oxygen concentration in the aeration tank with a control accuracy of ±0.2mg/l, improving the treatment efficiency of the biological treatment tank; optimizing the control of the blower, and reducing the plant's operating costs. The author's innovations: using advanced control algorithms and intelligent models to accurately control the dissolved oxygen concentration and adjust the blower pressure according to the valve opening, saving energy and reducing consumption. References [1] He Kezhong, Li Wei. Computer Control Principles [M]. Beijing: Tsinghua University Press, 2000. [2] Yu Guangping et al. Humanoid Intelligent PID Control and Its Application in Dissolved Oxygen Control in Wastewater Treatment [J]. Microcomputer Information, 2006, 1(1): 28-30 [3] Ding Fang et al. Application of Intelligent PID Algorithm in Liquid Level Control System [J]. 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