A method for controlling the concentration of suspended solids in the mixed liquor of a biological reactor based on a mathematical model of activated sludge

Abstract

This invention discloses a method for controlling the mixed liquor suspended solids (MLSS) concentration in a bioreactor based on an activated sludge mathematical model, comprising the following steps: S1, establishing and calibrating an activated sludge mathematical model; S2, setting a target MLSS concentration value for the bioreactor and collecting the MLSS concentration within the bioreactor; S3, calculating the current total mass of activated sludge based on the MLSS concentration and the effective volume of the bioreactor; S4, simulating and predicting the net increase in activated sludge volume within the most recent control period using the activated sludge mathematical model; S5, calculating the target sludge discharge mass for the next control period based on the simulation prediction results of the current total activated sludge mass and the net increase in activated sludge volume; S6, determining the sludge discharge flow rate based on the target sludge discharge mass and the real-time measured sludge concentration. This invention solves the problems of response lag, low adjustment accuracy, and poor adaptability to changes in influent load in existing activated sludge wastewater treatment processes.

Description

Technical Field

[0001] This invention relates to wastewater treatment control technology, and more specifically, to a method for controlling the concentration of suspended solids in the mixed liquor of a bioreactor based on a mathematical model of activated sludge. Background Technology

[0002] The activated sludge process is currently the most commonly used biological treatment process in wastewater treatment plants, and its operational stability largely depends on the control of the mixed liquor suspended solids (MLSS) concentration in the biological reactor.

[0003] In existing technologies, the main methods for controlling MLSS concentration include the following two:

[0004] (1) Manual control mode: The operator performs sludge discharge operation based on experience or a preset fixed sludge discharge plan. This mode is greatly affected by human factors, and the adjustment is lagging. It responds slowly to the dynamic changes in influent flow rate and pollutant load, which can easily lead to large fluctuations in MLSS concentration and affect the overall operational stability of the system.

[0005] (2) Automatic control based on online MLSS instruments and feedback controllers typically employs PI or PID controllers to adjust the sludge discharge rate according to the real-time measured MLSS concentration deviation. This method offers some improvement over manual control, but it is a typical feedback control. For biochemical systems like wastewater treatment processes, which exhibit significant inertia, time delay, and nonlinearity, feedback regulation responds slowly to disturbances. The system is prone to oscillations when the influent load changes, making it difficult to maintain a stable MLSS concentration near the target value over a long period.

[0006] However, the common problem with the two existing control methods mentioned above is that they are both passive post-event adjustments and lack the ability to effectively predict future sludge growth trends. Therefore, they are difficult to proactively adapt to the dynamic changes in influent water quality and quantity, which in turn affects the stability of effluent water quality and increases aeration energy consumption or sludge disposal costs. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method for controlling the mixed liquor suspended solids (MLSS) concentration in a biological reactor based on a mathematical model of activated sludge. This method solves the problems in existing activated sludge wastewater treatment processes, where MLSS concentration control is mostly based on manual experience or simple closed-loop control with feedback. These methods suffer from issues such as response lag, low adjustment accuracy, and poor adaptability to changes in influent load, making it difficult to achieve long-term stable control of MLSS concentration.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] A method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge includes the following steps:

[0010] S1, Establish and calibrate the mathematical model of activated sludge;

[0011] S2, Set the target MLSS concentration value for the bioreactor and collect the MLSS concentration in the bioreactor;

[0012] S3, Calculate the current total mass of activated sludge based on the MLSS concentration and the effective volume of the bioreactor;

[0013] S4. The net growth of activated sludge in the most recent control cycle is simulated and predicted using the activated sludge mathematical model.

[0014] S5. Based on the simulation prediction results of the current total mass of activated sludge and the net growth of activated sludge, calculate the target sludge discharge mass for the next control cycle.

[0015] S6. Determine the sludge discharge flow rate based on the target sludge discharge quality and the real-time measured sludge discharge concentration.

[0016] Preferably, in step S1, the mathematical model of the activated sludge is the ASM2d model;

[0017] The key dynamic parameters of the ASM2d model were locally calibrated using historical operating data and real-time monitoring data from the wastewater treatment plant.

[0018] The key kinetic parameters include the maximum specific growth rate of heterotrophic bacteria μ_mH, the heterotrophic bacteria yield coefficient Y_H, the heterotrophic bacteria endogenous decay coefficient b_H, the maximum specific growth rate of autotrophic bacteria μ_mA, the autotrophic bacteria yield coefficient Y_A, the autotrophic bacteria endogenous decay coefficient b_A, and the maximum specific hydrolysis rate K_h.

[0019] Preferably, in step S2, the relevant operating parameters in the bioreactor include influent flow rate Q_in, influent chemical oxygen demand (COD_in), influent ammonia nitrogen concentration (NH4_in), influent total phosphorus concentration (TP_in), dissolved oxygen concentration (DO) in each compartment of the bioreactor, mixed liquor return ratio R_inner, and sludge return ratio R_outer.

[0020] The relevant operating parameters within the bioreactor serve as real-time input boundary conditions for the activated sludge mathematical model, and are used in step S4 to simulate and predict the net growth of activated sludge.

[0021] Preferably, in step S3, the calculation expression for the current total mass of activated sludge m_current is:

[0022] m_current = MLSS_meas × V_eff

[0023] In the formula, MLSS_meas is the concentration of suspended solids in the mixed liquor of the bioreactor, measured in real time by a calibrated online MLSS instrument, in g / m³. 3 V_eff is the effective volume of the bioreactor, in m³. 3 The unit of m_current is kg, which is g / m 3 ×m 3 Divide the result by 1000 to convert it to kg.

[0024] Preferably, in step S4, the simulation prediction specifically includes:

[0025] The relevant operating parameters in the bioreactor are used as real-time input boundary conditions for the activated sludge mathematical model, driving the activated sludge mathematical model to perform dynamic simulation calculations, which are updated every hour.

[0026] The net growth rate of activated sludge, m_growth, is obtained by integrating and summing the net sludge generation rates over all times within the control period T_c: m_growth = Σ(r_grow,t × V_eff × Δt).

[0027] Where r_grow,t is the net growth rate of activated sludge at time t calculated by the activated sludge mathematical model, with a value of kg / (m³·h); Δt=1h, and the summation range is the entire control period T_c.

[0028] Preferably, in step S5, the calculation expression for the target sludge discharge mass in the next control cycle is:

[0029] Φ_w_set=(m_current+m_growth)-m_set

[0030] In the formula, Φ_w_set is the target sludge mass for the next control cycle, in kg; m_current is the current total activated sludge mass at the initial moment of the current control cycle calculated in step S3, in kg; m_growth is the net increase in activated sludge within the most recent control cycle predicted by simulation in step S4, in kg; and m_set is the target total sludge mass calculated based on the target MLSS concentration setpoint MLSS_set and the effective volume of the bioreactor V_eff, i.e., m_set = MLSS_set × V_eff, in kg.

[0031] Preferably, in step S6, the sludge concentration C_w is the residual sludge suspended solids concentration detected in real time by an online sludge concentration meter installed on the sludge discharge pipe, in units of kg / m³. 3 ;

[0032] The expression for calculating the sludge discharge flow rate Q_w is:

[0033] Q_w = Φ_w_set / (C_w × T_c)

[0034] In the formula, Q_w is the sludge discharge flow rate, in m³ / s. 3 / h; Φ_w_set is the target sludge discharge mass, in kg; C_w is the concentration of discharged sludge, in kg / m³. 3 T_c is the control cycle duration, in hours (h).

[0035] Preferably, the method for controlling the suspended solids concentration in the mixed liquor of the bioreactor further includes:

[0036] The cumulative deviation between the actual sludge discharge quality and the target sludge discharge quality calculated by the activated sludge mathematical model is monitored. When the cumulative deviation exceeds a preset threshold, the sludge discharge command for subsequent control cycles is compensated and adjusted.

[0037] Preferably, the supplementary adjustments to the sludge discharge instructions in subsequent control cycles specifically include:

[0038] (1) Using a fixed time window as the statistical period, record the target sludge discharge mass Φ_w_set(i) and the actual sludge discharge mass Φ_w_actual(i) calculated by the activated sludge mathematical model in each statistical period;

[0039] (2) Calculate the cumulative deviation ΔM=Σ(Φ_w_set(i)-Φ_w_actual(i)), i=1 to n, where n is the number of statistical periods;

[0040] (3) When the cumulative deviation ΔM exceeds the preset threshold, the constraint adjustment mode is triggered;

[0041] (4) Under the constraint adjustment mode, the target sludge discharge quality for the next control cycle is compensated and adjusted according to the current cumulative deviation ΔM:

[0042] The actual sludge discharge mass of the next control cycle = Φ_w_set(i) + ΔM;

[0043] (5) If compensation and sludge discharge cannot be carried out on site, a prompt should be sent to the operators through the host computer or alarm interface, and temporary measures should be recommended.

[0044] The present invention provides a method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge, which has the following beneficial effects:

[0045] (1) By adopting sludge growth prediction and feedforward sludge discharge control based on activated sludge mathematical model, the present invention can effectively reduce the impact of influent water quality and quantity fluctuations on the MLSS concentration of the biological tank, so that the MLSS concentration is maintained near the target set value under most operating conditions, and the fluctuation range is significantly reduced compared with the existing feedback control method, thereby improving the operational stability of the biological reaction system.

[0046] (2) Based on the present invention, different sludge concentrations can be set to adapt to the operating conditions of the season in different seasons, and the automatic control of the discharge of residual sludge in the sewage treatment process can be realized through automatic simulation calculation of the algorithm.

[0047] (3) The present invention adopts a sludge discharge calculation method based on direct model prediction. The control logic is clear and explicit, and there is no need to perform complex parameter tuning of the traditional PI / PID controller, which reduces the debugging difficulty and maintenance workload of the system. In addition, the simulation calculation frequency mentioned in this method is 1 hour, which can respond to the impact of influent water quality and quantity more promptly compared with the traditional feedback sludge discharge control method.

[0048] (4) The present invention mentions that regular calibration of online MLSS, determination of influent organic matter composition and determination of SVI can greatly improve the control effect and ensure the stability of MLSS in biological ponds.

[0049] (5) A stable MLSS concentration is conducive to providing a relatively constant growth environment for functional microorganisms such as nitrifying bacteria, which helps maintain and improve the denitrification efficiency of the system. At the same time, stable operating conditions help improve the settling performance of activated sludge, reduce the probability of abnormal phenomena such as filamentous bulking and biological foaming, and thus help ensure the long-term stable compliance of effluent quality. In addition, by controlling the sludge discharge rate more precisely, it is possible to avoid the increase in sludge disposal volume caused by excessive sludge discharge, and the increase in aeration energy consumption caused by high MLSS concentration due to insufficient sludge discharge. Thus, while ensuring the treatment effect, it helps to achieve comprehensive savings in aeration energy consumption and sludge disposal costs. Attached Figure Description

[0050] Figure 1 This is a schematic flowchart of the method for controlling the concentration of suspended solids in the mixed liquor of the bioreactor according to the present invention. Detailed Implementation

[0051] To better understand the above-mentioned technical solutions of the present invention, the technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0052] Combination Figure 1 As shown, this invention provides a method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge, comprising the following steps:

[0053] S1. Establish and calibrate an activated sludge mathematical model suitable for the target wastewater treatment plant. The ASM2d model is adopted, and the key kinetic parameters of the ASM2d model are localized using historical operation data and real-time monitoring data of the wastewater treatment plant.

[0054] S2, set the target MLSS concentration value MLSS_set for the bioreactor, and collect the MLSS concentration and related operating parameters in the bioreactor in real time through online sensors;

[0055] S3, calculate the current total mass of activated sludge m_current based on the MLSS concentration and the effective volume of the bioreactor;

[0056] S4 uses a calibrated activated sludge mathematical model, combined with the current influent flow and quality (including total influent flow, biological tank water distribution, and influent organic matter composition ratio) and process control conditions (biological reactor operation boundaries such as aeration, chemical dosing, and recirculation), to simulate and predict the net growth of activated sludge m_growth within the most recent control cycle (e.g., 24 hours); the activated sludge mathematical model is dynamically calculated once per hour.

[0057] S5, based on the simulation prediction results of the current total activated sludge mass m_current and the net growth of activated sludge m_growth, calculate the target sludge discharge mass Φ_w_set for the next control cycle, specifically:

[0058] Φ_w_set=(m_current+m_growth)-m_set

[0059] In the formula, m_set is the current total mass of activated sludge calculated in step S3;

[0060] S6 determines the sludge discharge flow rate based on the target sludge discharge mass Φ_w_set and the real-time measured external sludge concentration. The automatic control program determines the sludge discharge pump operating parameters (number of pumps to start and pump start time) and finally issues control commands to execute the sludge discharge operation.

[0061] In step S1 above, the ASM2d model is the second-generation extended version of the activated sludge model. It is an existing mathematical model of activated sludge developed by the International Water Association (IWA) and can describe a variety of biochemical processes such as carbon oxidation, nitrification, denitrification and biological phosphorus removal.

[0062] Key kinetic parameters include the maximum specific growth rate of heterotrophic bacteria μ_mH, the heterotrophic bacteria yield coefficient Y_H, the heterotrophic bacteria endogenous decay coefficient b_H, the maximum specific growth rate of autotrophic bacteria μ_mA, the autotrophic bacteria yield coefficient Y_A, the autotrophic bacteria endogenous decay coefficient b_A, and the maximum specific hydrolysis rate K_h.

[0063] In step S2 above, the relevant operating parameters in the bioreactor include influent flow rate Q_in, influent chemical oxygen demand (COD_in), influent ammonia nitrogen concentration (NH4_in), influent total phosphorus concentration (TP_in), dissolved oxygen concentration (DO) in each compartment of the bioreactor, mixed liquor return ratio R_inner, and sludge return ratio R_outer.

[0064] The relevant operating parameters within the bioreactor serve as real-time input boundary conditions for the activated sludge mathematical model, and are used in step S4 to simulate and predict the net growth of activated sludge.

[0065] In step S3 above, the expression for calculating the current total mass of activated sludge, m_current, is:

[0066] m_current = MLSS_meas × V_eff

[0067] In the formula, MLSS_meas is the concentration of suspended solids in the mixed liquor of the bioreactor, measured in real time by a calibrated online MLSS instrument, in g / m³. 3 V_eff is the effective volume of the bioreactor, in m³. 3 The unit of m_current is kg, which is g / m 3 ×m 3 Divide the result by 1000 to convert it to kg.

[0068] In step S4 above, the simulation prediction specifically includes:

[0069] The relevant operating parameters in the bioreactor are used as real-time input boundary conditions for the activated sludge mathematical model, driving the activated sludge mathematical model to perform dynamic simulation calculations, which are updated every hour.

[0070] The net growth rate of activated sludge, m_growth, is obtained by integrating and summing the net sludge generation rates over all times within the control period T_c: m_growth = Σ(r_grow,t × V_eff × Δt).

[0071] Where r_grow,t is the net growth rate of activated sludge at time t calculated by the activated sludge mathematical model, with a value of kg / (m³·h); Δt=1h, and the summation range is the entire control period T_c.

[0072] In step S4 above, when using the activated sludge mathematical model for simulation calculations, it is necessary to ensure that the input boundaries affecting the simulated sludge production are true and reliable. If necessary, the following three points should be noted in addition:

[0073] (1) Regularly test the proportion of organic components in the influent (refer to the methods recommended by the International Water Association);

[0074] (2) Regularly calibrate the online MLSS instrument based on the MLSS test values ​​of the biological pool;

[0075] (3) Supplement the SVI information of the biological tank sludge (if the relevant online instruments are missing) to improve the simulation accuracy of the sludge-water separation model of the secondary sedimentation tank.

[0076] In step S5 above, the calculation expression for the target sludge discharge mass of the next control cycle is as follows:

[0077] Φ_w_set=(m_current+m_growth)-m_set

[0078] In the formula, Φ_w_set is the target sludge mass for the next control cycle, in kg; m_current is the current total activated sludge mass at the initial moment of the current control cycle calculated in step S3, in kg; m_growth is the net increase in activated sludge within the most recent control cycle predicted in step S4, in kg; m_set is the target total sludge mass calculated based on the target MLSS concentration setpoint MLSS_set and the effective volume V_eff of the bioreactor, i.e., m_set = MLSS_set × V_eff, in kg. Here, m_current is the real-time measured calculated value, and m_set is the target value. The two have different meanings; the former changes with the actual operating status, while the latter is determined by the MLSS target value set by the operator.

[0079] In step S6 above, the sludge discharge concentration C_w is the concentration of suspended solids in the residual sludge, which is detected in real time by an online sludge concentration meter installed on the sludge discharge pipeline, in kg / m³. 3 This is different from the MLSS concentration in the biological reactor: the former is the sludge concentration in the sludge discharge pipeline after gravity thickening or recirculation, while the latter is the mixed liquor concentration in the reactor.

[0080] The expression for calculating the sludge discharge flow rate Q_w is:

[0081] Q_w = Φ_w_set / (C_w × T_c)

[0082] In the formula, Q_w is the sludge discharge flow rate, in m³ / s. 3 / h; Φ_w_set is the target sludge discharge mass, in kg; C_w is the concentration of discharged sludge, in kg / m³. 3 T_c represents the control cycle duration in hours (h). The automatic control program calculates the number of pumps to be started and their operating duration based on the above Q_w calculation results and the rated flow rate of the on-site sludge pumps, and then issues control commands to complete the sludge discharge operation.

[0083] Since the limited sludge treatment capacity leads to the problem of timely sludge discharge, it is necessary to set up a sludge total volume constraint and adjustment module. The method for controlling the suspended solids concentration of mixed liquor in the biological reactor of this invention also includes:

[0084] The module monitors the cumulative deviation between the actual sludge discharge quality and the target sludge discharge quality calculated by the activated sludge mathematical model. When the cumulative deviation exceeds a preset threshold, the sludge discharge instructions for subsequent control cycles are adjusted accordingly. This module is used to address situations where the processing capacity of on-site sludge treatment facilities (such as sludge thickening, dewatering, and storage) is limited, resulting in the actual sludge discharge volume being less than the sludge discharge volume calculated by the model.

[0085] The supplementary adjustments to the sludge discharge instructions in subsequent control cycles specifically include:

[0086] (1) Using a fixed time window (e.g., the most recent 24 hours) as the statistical period, record the target sludge discharge mass Φ_w_set(i) and the actual sludge discharge mass Φ_w_actual(i) calculated by the activated sludge mathematical model in each statistical period;

[0087] (2) Calculate the cumulative deviation ΔM=Σ(Φ_w_set(i)-Φ_w_actual(i)), i=1 to n, where n is the number of statistical periods;

[0088] (3) When the cumulative deviation ΔM exceeds the preset threshold (for example, ΔM ≥ 5%~10% of the target total sludge mass m_set, the threshold can be set by the operator according to the actual situation on site), the constraint adjustment mode is triggered;

[0089] (4) In the constrained adjustment mode, the target sludge discharge quality for the next control cycle is compensated and adjusted based on the current cumulative deviation ΔM:

[0090] The actual sludge discharge mass of the next control cycle = Φ_w_set(i) + ΔM;

[0091] (5) If the compensation sludge discharge cannot be carried out on site, a prompt should be sent to the operators through the host computer or alarm interface, and temporary measures should be recommended (such as increasing the number of sludge discharge shifts, coordinating external sludge disposal, etc.).

[0092] In summary, this invention uses an activated sludge mathematical model to predict future sludge growth and directly determine the sludge discharge rate. This falls under the category of feedforward + feedback control, where the feedforward mainly involves the dynamic simulation of sludge production from the activated sludge model, and the feedback is the actual MLSS concentration in the biological tank. Compared with existing control methods that mainly rely on feedback regulation, this invention has better response characteristics and stability when dealing with dynamic changes in influent load.

[0093] Example 1

[0094] This embodiment 1 takes a municipal wastewater treatment plant with a designed treatment capacity of 100,000 tons / day as an example, and uses A... 2 The wastewater treatment process of the O (anaerobic-anoxic-aerobic) process is described. The effective volume of the aerobic zone in this plant is 20,000 m³. 3 .

[0095] To control the MLSS concentration in the biological treatment tank, an ASM2d mathematical model was first adopted based on one year of historical operating data and real-time monitoring data from the wastewater treatment plant. Key kinetic parameters of the activated sludge mathematical model were then calibrated. The calibrated parameters include, but are not limited to: heterotrophic bacteria yield coefficient Y_H, decay coefficient b_H, maximum specific growth rate μ_mH, maximum specific growth rate of autotrophic bacteria μ_mA, and maximum specific hydrolysis rate K_h. The calibrated model effectively reflects the actual operating characteristics of the plant. The influent organic matter composition, SVI of the biological treatment tank, and the MLSS instrument in the biological treatment tank were recently measured, and the parameters were calibrated.

[0096] The target MLSS concentration in the aerobic tank was set at 3500 g / m³. 3 .

[0097] At the start of a certain control cycle (24 hours), the average MLSS concentration in the aerobic tank was measured to be 3500 g / m³ using a calibrated online MLSS meter. 3 Based on the effective volume of the aerobic tank of 20,000 m³ 3 The total mass of activated sludge in the current aerobic tank is calculated to be:

[0098] m_current=3500g / m 3 ×20000m 3 =70000kg

[0099] Based on the above calculation results, the PLC control system automatically controls the operating time and flow rate of the sludge discharge pump to complete the precise discharge of excess sludge.

[0100] In actual continuous operation, this control method maintains the MLSS concentration in the aerobic tank at 3500 g / m³. 3 The concentration remained relatively stable around the target value, with fluctuations generally controlled within ±10%. Consequently, the ammonia nitrogen concentration in the effluent was able to maintain a low level for an extended period under low-temperature conditions in winter (measured data consistently below 0.5 mg / L).

[0101] Example 2

[0102] This embodiment 2 also takes a municipal wastewater treatment plant with a designed treatment capacity of 100,000 tons / day as an example, and uses A... 2 The wastewater treatment process of the O (anaerobic-anoxic-aerobic) process is described. The effective volume of the aerobic zone in this plant is 20,000 m³.3 .

[0103] Under conditions of increased water temperature and influent load in summer (e.g., influent volume is 1.3 times the design volume), the activated sludge mathematical model still uses the same ASM2d model, but the target MLSS concentration is adjusted to 2800 g / m³. 3 Based on similar calculations in Example 1, the model predicts a net sludge growth of approximately 5.2 tons within 24 hours, therefore the calculated and executed sludge discharge mass is 5.2 tons.

[0104] The residual sludge concentration measured on-site using an online sludge concentration meter was 6000 mg / L (i.e., 6 kg / m³). 3 Based on this, the required volume of sludge to be discharged is calculated as follows:

[0105] Discharge volume = 5200 kg ÷ 6 kg / m³ 3 =866.67m 3 (approximately 867m) 3 ).

[0106] Those skilled in the art should recognize that the above embodiments are merely illustrative of the present invention and are not intended to limit the present invention. Any variations or modifications to the above embodiments that are within the spirit and essence of the present invention will fall within the scope of the claims of the present invention.

Claims

1. A method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge, characterized in that, Includes the following steps: S1, Establish and calibrate the mathematical model of activated sludge; S2, Set the target MLSS concentration value for the bioreactor and collect the MLSS concentration in the bioreactor; S3, Calculate the current total mass of activated sludge based on the MLSS concentration and the effective volume of the bioreactor; S4. The net growth of activated sludge in the most recent control cycle is simulated and predicted using the activated sludge mathematical model. S5. Based on the simulation prediction results of the current total mass of activated sludge and the net growth of activated sludge, calculate the target sludge discharge mass for the next control cycle. S6. Determine the sludge discharge flow rate based on the target sludge discharge quality and the real-time measured sludge discharge concentration.

2. The method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge according to claim 1, characterized in that, In step S1, the mathematical model of the activated sludge adopts the ASM2d model; The key dynamic parameters of the ASM2d model were locally calibrated using historical operating data and real-time monitoring data from the wastewater treatment plant. The key kinetic parameters include the maximum specific growth rate of heterotrophic bacteria μ_mH, the heterotrophic bacteria yield coefficient Y_H, the heterotrophic bacteria endogenous decay coefficient b_H, the maximum specific growth rate of autotrophic bacteria μ_mA, the autotrophic bacteria yield coefficient Y_A, the autotrophic bacteria endogenous decay coefficient b_A, and the maximum specific hydrolysis rate K_h.

3. The method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge according to claim 1, characterized in that, In step S2, the relevant operating parameters in the bioreactor include influent flow rate Q_in, influent chemical oxygen demand (COD_in), influent ammonia nitrogen concentration (NH4_in), influent total phosphorus concentration (TP_in), dissolved oxygen concentration (DO) in each compartment of the bioreactor, mixed liquor return ratio R_inner and sludge return ratio R_outer. The relevant operating parameters within the bioreactor serve as real-time input boundary conditions for the activated sludge mathematical model, and are used in step S4 to simulate and predict the net growth of activated sludge.

4. The method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge according to claim 1, characterized in that, In step S3, the calculation expression for the current total mass of activated sludge m_current is: m_current = MLSS_meas × V_eff In the formula, MLSS_meas is the concentration of suspended solids in the mixed liquor of the bioreactor, measured in real time by a calibrated online MLSS instrument, in g / m³. 3 V_eff is the effective volume of the bioreactor, in m³. 3 The unit of m_current is kg, which is g / m 3 ×m 3 Divide the result by 1000 to convert it to kg.

5. The method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge according to claim 3, characterized in that, In step S4, the simulation prediction specifically includes: The relevant operating parameters in the bioreactor are used as real-time input boundary conditions for the activated sludge mathematical model, driving the activated sludge mathematical model to perform dynamic simulation calculations, which are updated every hour. The net growth rate of activated sludge, m_growth, is obtained by integrating and summing the net sludge generation rates over all times within the control period T_c: m_growth = Σ(r_grow,t × V_eff × Δt). Where r_grow,t is the net growth rate of activated sludge at time t calculated by the activated sludge mathematical model, with a value of kg / (m³·h); Δt=1h, and the summation range is the entire control period T_c.

6. The method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge according to claim 1, characterized in that, In step S5, the calculation expression for the target sludge discharge mass in the next control cycle is: Φ_w_set=(m_current+m_growth)-m_set In the formula, Φ_w_set is the target sludge mass for the next control cycle, in kg; m_current is the current total activated sludge mass at the initial moment of the current control cycle calculated in step S3, in kg; m_growth is the net increase in activated sludge within the most recent control cycle predicted in step S4, in kg; and m_set is the target total sludge mass calculated based on the target MLSS concentration setpoint MLSS_set and the effective volume V_eff of the bioreactor, i.e., m_set = MLSS_set × V_eff, in kg.

7. The method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge according to claim 1, characterized in that, In step S6, the discharged sludge concentration C_w is the residual sludge suspended solids concentration detected in real time by an online sludge concentration meter installed on the sludge discharge pipeline, with units of kg / m³. 3 ; The expression for calculating the sludge discharge flow rate Q_w is: Q_w = Φ_w_set / (C_w × T_c) In the formula, Q_w is the sludge discharge flow rate, in m³ / s. 3 / h; Φ_w_set is the target sludge discharge mass, in kg; C_w represents the concentration of discharged sludge, in kg / m³. 3 ; T_c is the control cycle duration, in hours (h).

8. The method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge according to claim 1, characterized in that, The method for controlling the suspended solids concentration in the mixed liquor of the bioreactor also includes: The cumulative deviation between the actual sludge discharge quality and the target sludge discharge quality calculated by the activated sludge mathematical model is monitored. When the cumulative deviation exceeds a preset threshold, the sludge discharge command for subsequent control cycles is compensated and adjusted.

9. The method for controlling the suspended solids concentration in the mixed liquor of a bioreactor based on a mathematical model of activated sludge according to claim 8, characterized in that, The supplementary adjustments to the sludge discharge instructions in subsequent control cycles specifically include: (1) Using a fixed time window as the statistical period, record the target sludge discharge mass Φ_w_set(i) and the actual sludge discharge mass Φ_w_actual(i) calculated by the activated sludge mathematical model in each statistical period; (2) Calculate the cumulative deviation ΔM=Σ(Φ_w_set(i)-Φ_w_actual(i)), i=1 to n, where n is the number of statistical periods; (3) When the cumulative deviation ΔM exceeds the preset threshold, the constraint adjustment mode is triggered; (4) Under the constraint adjustment mode, the target sludge discharge quality for the next control cycle is compensated and adjusted according to the current cumulative deviation ΔM: The actual sludge discharge mass of the next control cycle = Φ_w_set(i) + ΔM; (5) If compensation and sludge discharge cannot be carried out on site, a prompt should be sent to the operators through the host computer or alarm interface, and temporary measures should be recommended.

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