废水处理过程的抗扰控制研究

doi:10.11949/0438-1157.20201664

摘要/Abstract

摘要：

厌氧消化废水处理过程中，动态变化的进水组分、组分浓度，组分间耦合等各种不确定因素，使得简单的闭环控制无法获得理想的污水处理效果。为使污水处理出水水质达标，对污水处理过程模型依赖小、对各种变化（扰动）因素鲁棒性强、动态响应好的控制方法可满足工程要求。为此，设计一种能够主动估计并消除扰动的抗扰控制方法，有效估计并补偿污水处理过程中存在的各种不确定因素，以获得期望的污水处理效果。数值仿真结果表明，抗扰控制具有较好的抗干扰能力，能够满足控制要求，是一种可行的污水处理控制方案。

关键词: 废水, 厌氧, 消化过程, 抗扰, 控制

Abstract:

In the process of anaerobic digestion wastewater treatment, various uncertain factors such as dynamically changing influent components, component concentrations, and coupling between components, make simple closed-loop control unable to obtain ideal wastewater treatment effects. In order to obtain satisfied effluent quality, a control technique, which is of fast response and less dependent on a process model, robust enough to disturbances, is able to satisfy the requirements of the control engineering. For the sake of achieving satisfied regulation, a disturbance rejection control, which estimates and cancels out the disturbance actively, is designed to regulate the output pollution level. The control technique utilized is capable of estimating and cancelling out uncertainties in the anaerobic digestion wastewater treatment process effectively. For the power of the control technique, the output pollution can be guaranteed in a desired level. Numerical results show that, the disturbance rejection control is robust enough to disturbances, and the closed-loop system performance can be guaranteed. It may be a feasible approach in the wastewater treatment process.

Key words: wastewater, anaerobic, digestion treatment processes, disturbance rejection, control

中图分类号:

魏伟, 蔡欣宇, 刘载文, 左敏. 废水处理过程的抗扰控制研究[J]. 化工学报, 2021, 72(3): 1567-1574.

WEI Wei, CAI Xinyu, LIU Zaiwen, ZUO Min. Disturbance rejection control for wastewater treatment processes[J]. CIESC Journal, 2021, 72(3): 1567-1574.

图/表 9

表1 生物过程参数

Table 1 Biological process parameters

产率系数	数值	动力系数和转换系数	数值
k₁	3.2	$μ 10$	0.2 h^-1
k₂	16.7	$μ 20$	0.5 h^-1
k₃	1.035	K_M1	0.75 g/L
k₄	1.194	K_M2	4 g/L
k₅	1.5	K_I2	21 g/L
k₆	3	ω₁	1.2
k₇	0.113	ω₂	1.75

表1 生物过程参数

Table 1 Biological process parameters

产率系数	数值	动力系数和转换系数	数值
k₁	3.2	$μ 10$	0.2 h^-1
k₂	16.7	$μ 20$	0.5 h^-1
k₃	1.035	K_M1	0.75 g/L
k₄	1.194	K_M2	4 g/L
k₅	1.5	K_I2	21 g/L
k₆	3	ω₁	1.2
k₇	0.113	ω₂	1.75

图1 厌氧废水处理过程输出污染物抗扰控制

Fig.1 Disturbance rejection control of the output pollutions in an anaerobic wastewater treatment process

表2 EFL、PI与DRC控制参数

Table 2 Control parameters of EFL, PI and DRC

控制器	控制参数
EFL	λ_i =5.5
PI	k_p=1, T_i =1
DRC	k₀=2, h₀=2

图2 设定的输出污染水平

Fig.2 Set values of the pollution levels

图3 进水底物浓度

Fig.3 Influent substrate concentrations

图4 理想情况下污染水平控制效果及控制信号

Fig.4 Pollution levels and control signals in an ideal case

表3 理想情况下的ITAE与IAE指标

Table 3 ITAE and IAE values in an ideal case

控制器	ITAE	ISE
EFL	7.3322	0.1327
PI	5.9346	0.0199
DRC	1.4899	0.0068

图5 加入扰动时的污染水平控制效果及控制信号

Fig.5 Pollution levels and control signals in presence of disturbances

表4 扰动情况下的ITAE与IAE指标

Table 4 ITAE and IAE values in presence of disturbances

控制器	ITAE	ISE
EFL	6.1745×10³	109.4598
PI	642.0027	1.1917
DRC	161.2388	0.0804

参考文献 21

1	周晋宇. 城市水环境修复与综合治理措施[J]. 环境与发展, 2019, 31(9): 219-221.
	Zhou J Y. Urban water environment restoration and comprehensive treatment measures[J]. Environment and Development, 2019, 31(9): 219-221.
2	何丽芳. 我国工业园区水污染现状及防治措施[J]. 当代化工研究, 2020, 56(3): 97-98.
	He L F. Water pollution status and prevention measures in industrial parks in China[J]. Modern Chemical Research, 2020, 56(3): 97-98.
3	孙华杰. 我国水污染的主要成因及防治对策[J]. 环境与发展, 2019, 31(9): 57-58.
	Sun H J. The main cause of water pollution in China and its prevention and control measures[J]. Environment and Development, 2019, 31(9): 57-58.
4	Angulo F, Olivar G, Rincon A. Control of an anaerobic upflow fixed bed bioreactor[C]//Proc. 15th Mediterranean Conference on Control & Automation. Athens, Greece: IEEE, 2007: T04-005.
5	Petre E, Selişteanu D, Sendrescu D. Adaptive and robust-adaptive control strategies for anaerobic wastewater treatment bioprocesses[J]. Chemical Engineering Journal, 2013, 217(1): 363-378.
6	Petre E, Selişteanu D, Şendrescu D, et al. An adaptive control structure for an anaerobic digestion process with unknown inputs[C]// International Carpathian Control Conference (ICCC). Sinaia, Romania: IEEE, 2017: 58-63.
7	Sastry S S, Isidori A. Adaptive control of linearizable systems[J]. IEEE Transactions on Automatic Control, 1989, 34(11): 1123-1131.
8	Petre E, Selisteanu D, Sendrescu D. Adaptive control strategies for a class of anaerobic depollution bioprocesses[C]// Proceedings of the International Conference on Automation, Quality and Testing, Robotics AQTR. Cluj-Napoca, Romania: IEEE, 2008: 159-164.
9	Selişteanu D, Petre E, Rǎsvan V B. Sliding mode and adaptive sliding-mode control of a class of nonlinear bioprocesses[J]. International Journal of Adaptive Control & Signal Processing, 2007, 21(8/9): 795-822.
10	Petre E, Selişteanu D, Şendrescu D, et al. Nonlinear and neural networks based adaptive control for a wastewater treatment bioprocess[C]// Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II. Springer Berlin Heidelberg, 2008: 273-280.
11	Petre E, Selişteanu D. A multivariable robust-adaptive control strategy for a recycled wastewater treatment bioprocess[J]. Chemical Engineering Science, 2013, 90(3): 40-50.
12	Petre E, Selişteanu D, Şendrescu D, et al. Neural networks-based adaptive control for a class of nonlinear bioprocesses[J]. Neural Computing & Applications, 2010, 19(2): 169-178.
13	魏伟, 左敏, 李伟, 等. 污水处理过程溶解氧浓度的自抗扰控制[J]. 控制理论与应用, 2018, 35(1): 24-30.
	Wei W, Zuo M, Li W, et al. Control of dissolved oxygen for a wastewater treatment process by active disturbance rejection control approach[J]. Control Theory & Applications, 2018, 35(1): 24-30.
14	Wei W, Chen N, Zuo M, et al. Disturbance rejection control for the dissolved oxygen in a wastewater treatment process[J]. Measurement and Control, 2020, 53(5/6): 899-907.
15	Wei W, Chen N, Zhang Z Y, et al. U-model based active disturbance rejection control for the dissolved oxygen in a wastewater treatment process[J]. Mathematical Problems in Engineering, 2020, 2020(7): 350791001-350791014.
16	魏伟, 陈楠, 左敏, 等. 基于复合抗扰的溶解氧浓度控制[J]. 控制理论与应用, 2020, 37(9): 1895-1903.
	Wei W, Chen N, Zuo M, et al. Compound disturbance rejection control of dissolved oxygen concentration[J]. Control Theory & Applications, 2020, 37(9): 1895-1903.
17	Wei W, Xia P F, Liu Z W, et al. A modified active disturbance rejection control for a wastewater treatment process[J]. Chinese Journal of Chemical Engineering, 2020, 28(10): 2607-2619.
18	胡超. 厌氧消化系统模型动态模拟和稳定性评价指标体系的研究[D]. 北京: 中国科学院大学, 2018.
	Hu C. Study on dynamic simulation of anaerobic digestion system model (ADSM) and process stability evaluation index[D]. Beijing: University of Chinese Academy of Sciences, 2018.
19	Bernard O, Hadj-Sadok Z, Dochain D, et al. Dynamical model development and parameter identification for an anaerobic wastewater treatment process[J]. Biotechnology and Bioengineering, 2001, 75(4): 424-438.
20	Batstone D J, Keller J, Angelidaki I, et al. The IWA anaerobic digestion Model No. 1 (ADM1)[J]. Water Science and Technology, 2002, 45(10): 65-73.
21	Tornambe A. A decentralized controller for the robust stabilization of a class of MIMO dynamical systems[J]. Journal of Dynamic Systems, Measurement, and Control, 1994, 116(6): 293-304.

[1]	康飞, 吕伟光, 巨锋, 孙峙. 废锂离子电池放电路径与评价研究[J]. 化工学报, 2023, 74(9): 3903-3911.
[2]	杨百玉, 寇悦, 姜峻韬, 詹亚力, 王庆宏, 陈春茂. 炼化碱渣湿式氧化预处理过程DOM的化学转化特征[J]. 化工学报, 2023, 74(9): 3912-3920.
[3]	曹跃, 余冲, 李智, 杨明磊. 工业数据驱动的加氢裂化装置多工况切换过渡状态检测[J]. 化工学报, 2023, 74(9): 3841-3854.
[4]	杨欣, 彭啸, 薛凯茹, 苏梦威, 吴燕. 分子印迹-TiO₂光电催化降解增溶PHE废水性能研究[J]. 化工学报, 2023, 74(8): 3564-3571.
[5]	吕龙义, 及文博, 韩沐达, 李伟光, 高文芳, 刘晓阳, 孙丽, 王鹏飞, 任芝军, 张光明. 铁基导电材料强化厌氧去除卤代有机污染物：研究进展及未来展望[J]. 化工学报, 2023, 74(8): 3193-3202.
[6]	张艳梅, 袁涛, 李江, 刘亚洁, 孙占学. 高效SRB混合菌群构建及其在酸胁迫条件下的性能研究[J]. 化工学报, 2023, 74(6): 2599-2610.
[7]	胡南, 陶德敏, 杨照岚, 王学兵, 张向旭, 刘玉龙, 丁德馨. 铁炭微电解与硫酸盐还原菌耦合修复铀尾矿库渗滤水的研究[J]. 化工学报, 2023, 74(6): 2655-2667.
[8]	张兰河, 赖青燚, 王铁铮, 关潇卓, 张明爽, 程欣, 徐小惠, 贾艳萍. H₂O₂对SBR脱氮效率和污泥性能的影响[J]. 化工学报, 2023, 74(5): 2186-2196.
[9]	苏晓丹, 朱干宇, 李会泉, 郑光明, 孟子衡, 李防, 杨云瑞, 习本军, 崔玉. 湿法磷酸半水工艺考察与石膏结晶过程研究[J]. 化工学报, 2023, 74(4): 1805-1817.
[10]	闫新龙, 黄志刚, 胡清勋, 张新, 胡晓燕. Cu/Co掺杂多孔炭活化过硫酸盐降解水中硝基酚研究[J]. 化工学报, 2023, 74(3): 1102-1112.
[11]	张中秋, 李宏光, 石逸林. 基于人工预测调控策略的复杂化工过程多任务学习方法[J]. 化工学报, 2023, 74(3): 1195-1204.
[12]	张江淮, 赵众. 碳三加氢装置鲁棒最小协方差约束控制及应用[J]. 化工学报, 2023, 74(3): 1216-1227.
[13]	徐银, 蔡洁, 陈露, 彭宇, 刘夫珍, 张晖. 异相可见光催化耦合过硫酸盐活化技术在水污染控制中的研究进展[J]. 化工学报, 2023, 74(3): 995-1009.
[14]	黄玉龙, 吕凡, 仇俊杰, 章骅, 何品晶. 易腐垃圾厌氧消化沼液理化性质及VOCs分子特征[J]. 化工学报, 2023, 74(3): 1275-1285.
[15]	李承威, 骆华勇, 张铭轩, 廖鹏, 方茜, 荣宏伟, 王竞茵. 氢氧化镧交联壳聚糖微球的微流控制备及其除磷性能[J]. 化工学报, 2022, 73(9): 3929-3939.