城市污水处理过程污泥膨胀识别与抑制综述

污泥膨胀是活性污泥法污水处理过程中常见的一类异常工况, 且具有严重危害性, 研究污泥膨胀的识别和抑制方法对城市污水处理过程正常运行意义重大. 本文主要针对城市污水处理过程中污泥膨胀的识别和抑制方法进行综述. 首先, 文章概述了城市污水处理过程, 介绍了污泥膨胀的概念、主要特点、类型和成因; 其次, 概述了基于微生物生理特征、机理模型、图像识别和数据驱动的污泥膨胀识别方法, 分析其发展现状并指出优缺点; 然后, 概述了基于过程调控和机理特征的污泥膨胀抑制方法, 分析其发展现状并对比优缺点; 最后, 总结全文, 指出了城市污水处理过程污泥膨胀识别和抑制面临的主要问题, 并对其研究趋势进行了展望.     

基于S7-200 PLC的污水处理自控系统设计

项目主要运用西门子S7-200 PLC、变频技术、PID技术和触摸屏技术将污水处理系统的各子系统,如:污泥提升、污泥调理、污泥压滤、污泥压榨、管道反吹及滤布清洗等系统进行集中监控,大大提高了管理效率和污水处理系统的可靠性。     

基于微生物传感器的BOD分析仪的研制及应用

本文报道了以淀粉厂电性污泥中分离筛选出的单菌体经培养，固定化制成膜，贴装于氧电极表面制成ＢＯＤ传感顺，采用微电流放大器，流动注射成路系统，计算机综合控制等技术，建立了自动快速测定ＢＯＤ的新方法，该仪器具有自动校准，自动测量，自动记录结果等功能。仪器测量范围为０～１００ｍｇ．Ｌ＾－１，重复性为８％（Ｆ．ｓ）基本误差为±１０％（Ｆ．ｓ．）。该仪器已在生活污水处理长时期应用，其测量结果与ＢＯＤ５＾２０标     

计算机智能控制系统及其应用

根据某污水处理生产工艺流程的特点和生产过程控制的要求,结合我国污水生产厂的实际情况,采用“EIC三电一体化”计算机集散控制技术,设计整个污水处理生产过程的分布式计算机控制系统。在此基础上,通过采用优化设定控制技术、自适应自整定PI控制技术等先进技术,解决城市污水生产过程控制中存在的大滞后、非线性、耦合等关键技术问题,实现污水提升、浮选加药、污泥脱水等污水处理生产过程的自动控制。     

污水处理厂工程自动控制系统

根据唐山市玉田县当地污水水质情况,针对奥贝尔氧化沟污水处理工艺的特点及其处理过程对控制的要求,采用PLC以及其它控制元件,完成对污水处理装置中的粗处理装置、排污泵的启停,氧化沟及沉淀池的控制,以及回流污泥处理系统、除磷加药系统等过程的顺序控制.并对安全系统的紧急停车进行PLC控制处理,从而实现了安全、稳定、高效、低耗的目的.     

新疆阿克苏市污水处理厂自动控制系统

新疆阿克苏市污水处理厂今年正式开始运行，并获得了国家科技进步二等奖。污水处理采用了水解－SBR（UNITANK）好氧处理工艺，具备12万立方米的日处理能力。整个系统分进口预处理段、提升泵站配水井、水解池和污泥处理、SBR反应池和鼓风机房、变配电系统及井房等五大部分。由于工艺的需要，必须进行自动控制，其中进口预处理段提升泵站配水井、水解池和污泥处理、变配电系统及井房由“泵房”主站控制，共284个I/O点；SBR反应池和鼓风机房由揝BR池主站控制，共153个I/O点，工程总I/O点437个。 ◆ 用户需求 该自控系统共有11个控制…     

仿人智能模糊控制在污水处理中的应用

基于化工过程中污水处理的严重非线性，时间延迟、非参数模型等特性，使得采用常规的控制技术如ＰＩＤ，对ＰＨ值进行精密控制难以取得理想效果，提出了仿人智能模糊控制应用于污水处理，系统具有较强的鲁棒性和自适应性，现场运结果表明该系统具有优良的控制性能。     

嵌入式污水处理控制装置的设计

提出一种以ARM嵌入式系统为控制核心的实用新型污水处理控制装置。通过分析中小型城镇污水处理现状给出了嵌入式污水处理控制装置的硬件和软件设计方案。设计综合分析表明:该污水处理控制装置具有执行效率高、占用空间小、实时性优良和可扩展性强等优点。     

小型污水处理系统的自控装置研制

本文介绍为住宅小区的典型污水处理系统配置的一种自控装置。它由触摸屏和PLC等元件组成．取代传统的继电接触器控制装置。具有简单，方便，可靠等特点。文章在简述小型污水处理系统的基础上，论述了该自控装置的结构及工作原理。着重介绍F940WGOT触摸屏的画面制作功能，应用及设计时注意事项。     

基于国际评价基准的溶解氧控制方法研究

针对活性污泥污水处理过程溶解氧浓度(DO)控制的非线性特性，以DO为控制对象、国际评价基准（benchmark）为平台，将PID控制、增益调度控制和一般模型控制(GMC)方法应用于DO控制中，并进行了控制器性能的比较．仿真结果表明，所提一般模型非线性控制方法的性能优于其他两种控制方法，体现出该方法的有效性和优越性．     

A nonlinear observer for activated sludge wastewater treatment process: Invariant observer

An activated sludge wastewater treatment process model is concerned in this paper. In order to estimate the variables that cannot be measured online, an invariant observer for activated sludge wastewater treatment process is presented. The invariant observer can measure biomass concentration, substrate concentration and dissolved oxygen concentration in high accuracy and rapidity. Meanwhile it can be structured by means of typical form, and its robust convergence property is verified by theoretical analysis and numerical simulations (MATLAB ).     

Dissolved oxygen control for activated sludge processes

Controllers for dissolved oxygen reference trajectory tracking for activated sludge processes are proposed and investigated. A nonlinear model predictive controller and a direct reference adaptive controller are investigated. Both the nutrient and the phosphorous removal from a wastewater by its biological treatment using an activated sludge technology are considered. An approach to the controller design utilises a structure of the dissolved oxygen dynamics and its two time scales: fast and slow. The predictive controllers offer good tracking performance and robustness. The direct model reference adaptive controller is much simpler to implement. However, it is more difficult to compromise between tracking accuracy and rate of change and magnitudes of the control actions. The controllers are validated by simulation using real data sets and an ASM2d model of the biological reactor.     

Prediction of activated sludge bulking based on a self-organizing RBF neural network

Despite extensive research that has been done on sludge bulking, it remains a widespread problem in the operation of activated sludge processes, which brings severe economic and environmental consequences. In this study, a self-organizing radial basis function (SORBF) neural network method is utilized to predict the evolution of the sludge volume index (SVI). The hidden nodes in the SORBF neural network can be grown or pruned based on the node activity (NA) and mutual information (MI) to achieve the appropriate network complexity and maintain overall computational efficiency. The growing and pruning criteria of the SORBF can vary its structure dynamically with the objective to enhance its performance. Moreover, the input–output selection to calculate the SVI values is also discussed. The variables with key relations to the sludge bulking are used as the inputs for the SVI. Finally, the SORBF neural network is applied to the activated sludge wastewater treatment processes (WWTPs) for predicting the SVI, and then for predicting the sludge bulking. Experimental results show the excellent performance of the SORBF method. The performance comparison demonstrates the effectiveness of the proposed SORBF.     

Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications.     

A constrained closed loop MPC based on positive invariance concept for a wastewater treatment plant

This paper presents a new methodology to design a closed loop model predictive control (CLMPC) using polyhedral invariant sets. This methodology gives a simple solution to this type of control, ensuring stability and respecting non-symmetrical constraints on control magnitudes, as well as moving in both modes of operation of the dual controller. The proposed algorithm takes advantage of the design of the state feedback control law in the CLMPC to increase the degrees of freedom, in contrast to other CLMPC approaches. In order to design the controller so that it respects constraints on both control magnitudes and its increments, necessary and sufficient conditions for asymptotic stability at the origin have been developed for linear systems. The controller is applied to an illustrative linear example and the activated sludge process in a wastewater treatment plant, showing the efficiency of the proposal.     

Transformers for interfacing anaerobic digestion models to pre- and post-treatment processes in a plant-wide modelling context

In view of the growing importance of integrated and plant-wide modelling of wastewater treatment plants, this work reviews, applies and compares two transforming/interfacing methods by connecting anaerobic digestion and activated sludge models. The two methods are systematic approaches to transform state variables of one model to another and vice versa. The theory of the first method was presented before (Vanrolleghem et al., 2005. Wat. Sci. Technol., 52(1–2), 493–500.) as a general approach for interfacing any two models presented by Petersen matrices. The present work is the first application and therefore validation of this general approach. The theory of the second method was specifically developed for connecting ASM1 and ADM1, both standard IWA models. As an illustration, in this work a specific simulation example is presented in which the COST/IWA activated sludge benchmark plant is extended by sludge treatment and digestion facilities.     

Fixed-order H 2 controller design for state space polytopic systems

In this article, the problem of fixed-order H ₂ controller design for continuous-time polytopic systems is investigated. It is assumed that the uncertain parameters appear in the state space realization of the system. A convex set of fixed-order H ₂ controllers is presented by introducing a slack matrix variable which decouples the Lyapunov variables and the controller parameters. Taking advantage of this feature, we can readily design a robust fixed-order controller for a polytopic system with non-common Lyapunov variables. An optimization problem is presented for computing the slack variables using an initial controller selected by the designer. Additionally, to improve the obtained performance, a procedure is provided to reduce the dependency of the method on the initial controller. The design conditions are in terms of solutions to a set of linear matrix inequalities. Numerical examples demonstrate the effectiveness of the proposed approach.     

基于行为方法的同时镇定

从行为角度研究了动态系统的互联与控制．通过把控制规定为一种互联,得到了使系统镇定的一些新结果,此时,控制器不过是限制对象行为的一个系统．通过潜在变量的消除,得到人们感兴趣的那部分变量的动态特性刻画：即可以通过极点配置变成稳定的．通过定义一个既单且满的Bezout映射,证明了该控制器能镇定系统的多样性.从而使得一个控制器能对两个或两个以上的系统同时镇定．仿真算例验证了设计的正确性和有效性．     

Service process control: conceptualising a service as a feedback control system

This paper shows how a service process can be recast into a feedback control structure and how chemical process control principles can be applied. The outputs of the ‘service plant’ are process characteristics that meet the requirements of the plant's various stakeholders; the manipulated and disturbance variables are those variables that are within and outside a service manager's control respectively; the model is a process flowchart; and the controller is the service manager. Good stability, performance and robustness are also required because customers value reliability, responsiveness, and consistency of service in the face of variations caused by involvement of people in the service delivery. To illustrate these concepts, a patient treatment process within an emergency ward was recast as a control system, and an off-line model-based optimal controller was applied to this stochastic process. The benefits of recasting services as feedback control systems flow both ways: service design and operation will be improved by the application of engineering principles; and chemical process control will benefit from techniques specially developed to handle market fluctuations.     

Multivariable control strategy based on bifurcation analysis of an industrial gas-phase polymerization reactor

In an industrial gas-phase polyethylene reactor, the safe operating range of temperature is rather narrow. Even within this temperature range, temperature excursions must be avoided because they can result in low catalyst productivity and significant changes in product properties. If the manipulated variable for temperature control saturates (i.e., the cooling water valve position is completely open), then the reactor operates without a feedback temperature controller, leading to oscillatory behavior and limit cycles. In this work, it has been demonstrated that the saturation in the manipulated variable and the complex non-linear dynamic behavior are removed when auxiliary manipulated variables, obtained by bifurcation analysis, are used in a multivariable control strategy for the reactor temperature control. Two control structures are proposed and compared considering their impact in the reactor production and polymer melt index. In the first control structure, the designed PID controller for the reactor temperature is considered and a switching strategy with a PI controller for the auxiliary manipulated variables is included. In the second control structure, the designed PID controller for the reactor temperature is also used, however, a MPC controller for the auxiliary manipulated variables is considered. The results suggest that the use of gain-scheduling strategy in the PID temperature controller with a MPC controller for the auxiliary manipulated variables avoids the saturation of the manipulated variable and, hence, the undesired non-linear dynamic behavior, reducing the production loss and improving the product quality.