Norhaliza Abdul Wahab

Aerobic sludge granulation at high temperatures for domestic wastewater treatment

With inoculum sludge from a conventional activated sludge wastewater treatment plant, three sequencing batch reactors (SBRs) fed with synthetic wastewater were operated at different high temperatures (30, 40 and 50±1°C) to study the formation of aerobic granular sludge (AGS) for simultaneous organics and nutrients removal with a complete cycle time of 3h. The AGS were successfully cultivated with influent loading rate of 1.6CODg(Ld)(-1). The COD/N ratio of the influent wastewater was 8. The results revealed that granules developed at 50°C have the highest average diameter, (3.36mm) with 98.17%, 94.45% and 72.46% removal efficiency observed in the system for COD, ammonia and phosphate, respectively. This study also demonstrated the capabilities of AGS formation at high temperatures which is suitable to be applied for hot climate conditions.

Multivariable PID control design for wastewater systems

This paper investigates the application of multivariable PID controllers to a wastewater treatment process. Four multivariable PID control schemes are investigated. The methods considered are those suggested by Davison, Penttinen-Koivo, Maciejowski and a new method proposed in this paper. All of the methods are suitable for multi-input multi-output (MIMO) control loops that experience loop interaction. The methods, furthermore, requires only simplistic plant models. The performance of the methods is assessed using a nonlinear benchmark model, and the optimal tuning values are determined using an optimisation method. The simulation results show the significance of the study and lead to the conclusion that the proposed method yields somewhat better results than other methods with respect to decoupling capabilities and closed-loop performance.

Fouling control strategy for submerged membrane bioreactor filtration processes using aeration airflow, backwash, and relaxation: a review

AbstractAs of today, the application of membrane bioreactors (MBRs) in wastewater treatment plants has become significantly important in various industries. The success of MBR is mainly because of the effective membrane technology used in this kind of reactor. However, membrane technology does not escape from several drawbacks, which includes high maintenance costs and fouling problems. In order to run a plant with both an optimum capability and cost, an in-depth understanding of the behavior of filtration systems is very important to the plant operator. In this paper, we review and have considered the fouling control techniques applied to submerged membrane filtration processes including hollow fiber membranes and flat sheet types of membrane filtration. The review covers the techniques involving operational parameters, such as aeration, backwashing, and relaxation. In addition, in this paper, the modeling techniques and available automatic control techniques, using stated parameters to control fouling i...

Particle Swarm Optimization for multivariable PID controller tuning

In this paper, the tuning of multivariable PID (MPID) controller using particle swarm optimisation (PSO) is presented. To provide better performance in the industry, MPID implementation often uses heuristic approach, which is based on experience. However, this method of tuning is time consuming and inadequate for complex systems. To obtain a better performance in decoupling capabilities and closed loop performance, in this study, the MPID parameters are fine-tuned using Multi-objective PSO. Simulation results show tuning parameters of MPID controllers obtained via PSO yield better performance when applied to nonlinear system for different control strategies.

Nonlinear PI Control with Adaptive Interaction Algorithm for Multivariable Wastewater Treatment Process

The wastewater treatment plant (WWTP) is highly known with the nonlinearity of the control parameters, thus it is difficult to be controlled. In this paper, the enhancement of nonlinear PI controller (ENon-PI) to compensate the nonlinearity of the activated sludge WWTP is proposed. The ENon-PI controller is designed by cascading a sector-bounded nonlinear gain to linear PI controller. The rate variation of the nonlinear gain is automatically updated based on adaptive interaction algorithm. Initiative to simplify the ENon-PI control structure by adapting has been proved by significant improvement under various dynamic influents. More than 30% of integral square error and 14% of integral absolute error are reduced compared to benchmark PI for DO control and nitrate in nitrogen removal control. Better average effluent qualities, less number of effluent violations, and lower aeration energy consumption resulted.

N4SID and MOESP subspace identification methods

Multivariable Output Error State Space (MOESP) and Numerical algorithms for Subspace State Space System Identification (N4SID) algorithms are two well known subspace identification techniques discussed in this paper. Due to the use of robust numerical tools such as QR decomposition and singular value decomposition (SVD), these identification techniques are often implemented for multivariable systems. Subspace identification algorithms are attractive since the state space form is highly suitable to estimate, predict, filters as well as for control design. In literature, there are several simulation studies for MOESP and N4SID algorithms performed in offline and online mode. In this paper, order selection, validity and the stability for both algorithms for model identification of a glass tube manufacturing process system is considered. The weighting factor α, used in online identification is obtained from trial and error and particle swarm optimization (PSO). Utilizing PSO, the value of α is determined in the online identification and a more accurate result with lower computation time is obtained.

Determination of Concentration Profile for Flowing Solid Particles in Pipeline Using Electric Charge Tomography System

Tomography aims to present an image of a cross-sectional distribution of materials in some regions of interest such as cross-section of a pipeline or process vessel. This paper presents the concentration profiles of solid particles across a conveying pipeline obtained using tomographic imaging. In the paper, 16 electrodynamic sensors were installed around the circumference of a pipeline to capture electric charges carried by the particles moving through the pipeline under gravity. The Cartesian coordinate system used to derive the system equation gave an accurate charge distribution while the meshing technique of the finite element method applied miniaturized the pixel sizes within the sensing zone. The problem of unstable matrix and weak signal response around the center of the pipe cross-section, normally associated with the electric charge tomography system, was addressed using matrix compression through transposition and filtering. The pro rata distribution method mostly applied in the financial accounting analysis was used in the final stage. An algorithm for realization of the concepts was developed using MATLAB. The qualities of the resulting images for four different flow regimes provide good quality images representing the distribution of the particles across the pipeline cross-section.

Multivariable PID control tuning: A controller validation approach

The proper tuning of multivariable PID controllers is not a straightforward task. This is specially true when data driven models and controller design methodologies are adopted to increase the industry acceptance of controller implementation and commissioning. On the other hand there are well established model based design methodologies which provide controllers of higher complexity. In this paper we propose a tuning methodology based on a PID controller matching to a figure of merit. Thus the PID tuning parameters are selected to minimize certain error metric when compared with an optimal controller. Moreover the index to be minimized is a residual that can be obtained from data. As a result it is possible to validate the proximity of the PID controller to the desired figure of merit in the frequency domain from data.

Feed-Forward Neural Network Approximation Applied to Activated Sludge System

The dynamic behavior of an activated sludge system is highly complex and uncertain. To efficiently control and operate the system, a reliable model capable of accurately describing the several time-varying parallel processes of the system is needed. Most of the existing models are too complex to use for design or control purposes. This paper presents a feed-forward neural network model for the system. The model validation was achieved through the use of appropriate international accepted data of the benchmark simulation model no. 1 (BSM1). Simulation studies revealed that the neural network model exhibited an outstanding performance in predicting the effluent quality, root mean square error (RMSE) of 0.0464, mean absolute deviation (MAD) of 0.0347, correlation coefficient (R) of 0.979 for chemical oxygen demand (COD) and RMSE of 0.1103, MAD of 0.0794, R of 0.841 for the total nitrogen (TN) could be acheived. The model is quite effective and suitable tool for the activated sludge system.

Multivariable PID control of an Activated Sludge Wastewater Treatment Process

In general, wastewater treatment plant (WWTP) consists of several stages before it is released to a receiving water body. There are, preliminary and primary treatment (mechanical treatment), a secondary treatment (biological treatment) and a tertiary treatment (chemical treatment). In this chapter, since the work involve of identification and control design of activated sludge process to improve the performance of the system, and most of the control priorities are centred on the biological treatment process, only the secondary treatment will be highlighted.