•An industrial SBR simulation model for paper mills was developed.•Sludge characteristic parameters were estimated and corrected with temperature.•Four COD fractions of the wastewater in paper mill were determined.•Simulated results with the field data could predict well the actual effluent COD.Being an internationally accepted standard for the activated sludge modeling, the Activated Sludge Model No.1 (ASM1) was used to simulate the treatment of paper mills effluent in an industrial full-scale sequencing batch reactor (SBR). Key characteristic parameters were estimated and corrected with the wastewater temperature: maximum heterotrophic growth rate μH (9.69/day), heterotrophic yield YH (0.625 g cell COD/g COD oxidized) and heterotrophic decay rate bH (1.98/day). The wastewater chemical oxygen demand (COD) was fractionated as slowly biodegradable substrate XS (20%), particulate inert organic matter XI (58%), readily biodegradable substrate SS (18%) and soluble inert organic matter SI (4%). Finally, the SBR operation was simulated with field data from the paper mill. The average relative error of the simulated effluent COD was 12.7%. The results showed that the ASM1 could be reasonably used in the papermaking wastewater treatment simulation.

We studied nitrate control strategies in an activated sludge wastewater treatment process (WWTP) based on the activated sludge model. Two control strategies, back propagation for proportional-integral-derivative (BP-PID) and adaptive-network based fuzzy inference systems (ANFIS), are applied in the WWTP. The simulation results show that the simple local constant setpoint control has poor control effects on the nitrate concentration control. However, the ANFIS (4*1) controller, which considers not only the local constant setpoint control of the nitrate concentration, but also three important indices in the effluent—ammonia concentration, total suspended sludge concentration and total nitrogen concentration—demonstrates good control performance. The results also prove that ANFIS (4*1) controller has better control performance than that of the controllers PI, BP-PID and ANFIS (2*1), and that the ANFIS (4*1) controller is effective in improving the effluent quality and maintaining the stability of the effluent quality.

•We presented a PCA-based diagnostic method for four sensors in WWTP.•Principal component (PC) loadings well represented the contributions of variables.•PC scores gave a clear indication of faulty samples.•Combination of score and loading of PC was used to determine the faulty location.This paper presents a PCA (principal component analysis)-based diagnostic approach, combining the principal component scores with the principal component loadings, to determine the fault location of sensors in a pilot-scale SBR (sequencing batch reactor activated sludge process) wastewater treatment process. The PCA diagnostic model is firstly built with the historical normal data, and the determination of fault location of sensors in wastewater treatment process is further achieved through the combination of the scores with the loadings of principal components. The study results reveal that PCA model can be used to detect faults; the loadings of principal components can well represent the contributions of variables to the principal components; and the scores of principal components give a clear indication of the faulty samples. The feasibility and effectiveness of the application of the combination of score plots with loading plots for sensor fault diagnosis in the wastewater treatment process are well demonstrated in the study.

Aiming at the difficulties and problems of online measurement of pulp Kappa number during batch pulping, a novel measuring idea was proposed to predict the lignin content in pulp through the measurement of dissolved lignin in cooking liquor with spectroscopic technology. It was discovered that the spectral absorption of sulfite cooking liquor from Masson’s pine in 460−580 nm wave range resulted mainly from lignin sulfonate with high molecular weight, while saccharide and water in sulfite cooking liquor have no obvious absorption. The delignification study shows that the sulfite cooking delignification process can be observed with selected visible wavelength. Mathematical models of online Kappa number determination with visible spectroscopy were developed by chemometrics for batch sulfite pulping. After applying to sulfite pulp mill, the results showed that the new measuring method was much better than the manual method: The first-class proportion of pulp has been improved from 55% to 70%, the pulp Kappa number could be controlled within ±2 units. With this new method, it is possible not only to measure sulfite pulp Kappa number but also to perform the end point controlling of the sulfite pulping process.

Aiming at the difficulties and problems of online measurement of pulp kappa number during batch pulping, this paper proposes a new measuring idea, which is to predict the lignin content in pulp through the measurement of dissolved lignin in cooking liquor with spectral technology. The basic and modified mathematical model of kappa number during sulfite pulping as well as the end point controlling model are put forward in detail. The site running result shows that the introduction of modified factor ε, which represents the change of the total lignin amount added into the digester, is effective. Therefore, the online measurement of kappa number and the determination of the end point of pulping can be achieved.

A cascade model predictive control (MPC) strategy is proposed to improve the control performance of the combined biological phosphorus and nitrogen removal in the anaerobic-anoxic-oxic (AAO) process. Owning the features of determining the capability of the current controller and locating the best achievable control performance, the control performance assessment technique (CPA) is used to determine the optimal tuning parameters of the cascade MPC controller. The plant performance of the proposed cascade controller is superior to the conventional decentralized controller in the AAO process. An improved performance of the suggested cascade MPC controller was obtained by using the CPA approach.

Being an optimizing technology, model predictive control (MPC) can now be found in a wide variety of application fields. The main and most obvious control goal to be achieved in a wastewater treatment plant is to fulfill the effluent quality standards, while minimizing the operational costs. In order to maintain the effluent quality within regulation-specified limits, the MPC strategy has been applied to the Benchmark Simulation Model 1 (BSM1) simulation benchmark of wastewater treatment process. After the discussion of open loop responses of outputs to manipulated inputs and measured influent disturbances, the strategies of feedback by linear dynamic matrix control (DMC), quadratic dynamic matrix control (QDMC) and nonlinear model predictive control (NLMPC), and improvement by feedforward based on influent flow rate or ammonium concentration have been investigated. The simulation results indicate that good performance was achieved under steady influent characteristics, especially concerning the nitrogen-related species. Compared to DMC and QDMC, NLMPC with penalty function brings little improvement. Two measured disturbances have been used for feedforward control, the influent flow rate and ammonium concentration. It is shown that the performance of feedforward with respect to the influent ammonium concentration is much higher than for the feedforward with respect to the influent flow rate. However, this latter is slightly better than the DMC feedback. The best performance is obtained by combining both feedforward controllers with respect to the influent ammonium concentration and flow rate. In all cases, the improvement of performance is correlated with more aeration energy consumption.