Zakariah Yusuf

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...

PID controller tuning for glycerin bleaching process using well-known tuning formulas- a simulation study

This paper presents a simulation study on PID controller tuning for glycerin bleaching process. The tuning was based on Ziegler-Nichols (Z-N), Cohen-Coon, Internal Model Controller (IMC), Integral of Absolute Error (IAE), Integral of Square Error (ISE) and Integral Time-Weight absolute Error (ITAE) methods. The control performance of each method was evaluated in term of percent overshoot, settling time and rise time. The simulated controller parameters were verified by testing on the actual plant using field instrument module and LabVIEW as interfacing system. The results revealed that the process was best tune using ITAE technique.

Self tuning PID controller for steam distillation essential oil extraction system

Controlling a temperature for a distillation system is not an easy task. The lag of this process is normally long. Over heating during the operation can cause quality degradation of the essential oil produced. The conventional method of controlling this kind of process is not capable of giving satisfactory result. In this paper the self tuning PID controller is developed to improvise the steam distillation temperature control. This paper is intended to compare the performance of PID, Fuzzy Logic and Self tuning PID controller in term of rise time, % overshoot and settling time. The ARX (Auto Regressive Exogenous) model has been utilized to represent the dynamic of the steam distillation process. From the simulation, it is clearly shown that self tuning PID controller give better performance compared with conventional Fuzzy logic and PID controller.

Application of Fuzzy Logic Controller for glycerin bleaching process

This paper describes the development of Fuzzy Logic Controller (FLC) for a glycerin bleaching process based on simulation study. The first order plus dead time (FPODT) model of the glycerin bleaching temperature is obtained using open loop step test from a glycerin bleaching pilot plant. Fuzzy PI and Fuzzy PD controller was developed to replace the existing PID controller. The performances of the controllers are measured and compared with conventional PID controller. The result shows the fuzzy logic controllers performed much better compared with a PID controller in controlling glycerin bleaching temperature.

A simulation study of Model Reference Adaptive Control on temperature control of glycerin bleaching process

Temperature plays a major role in determining the effectiveness of bleaching process. Poor temperature control will degrade the end product quality and this problem can be overcome by engaging a robust temperature control. However, since the nature of bleaching process possess large time delay and unknown dynamic variations or uncertainties, it is inherently difficult to design a good temperature controller and simultaneously maintain the desired transient performance aspect. This paper presents the preliminary study of Model Reference Adaptive Control (MRAC) implementation in temperature control of glycerin bleaching process. Open loop step test data is used to construct the Auto-Regressive with Exogenous Input (ARX) corresponding model. The MRAC approach based on Lyapunov rule was tested and analyzed. Simulation results show that, through proper selection of adaptation gain, MRAC is capable to provide excellent temperature regulating performance and also proficient in sustaining the excellent performance under set point change.

Application of Fuzzy PD controller with Smith Predictor for glycerin bleaching temperature control

Controlling a temperature for a large system is not an easy task, the lag is big and the overshoot is high. The conventional method of controlling this kind of process is not capable of giving satisfactory result. In this paper the implementation of Fuzzy Logic controller with Smith Predictor is an alternative to control this system. First order plus dead time model (FOPDT) is used for simulation. Fuzzy PD with Smith Predictor is developed using 3 (Fuzzy PD3-SP), 5 (Fuzzy PD5-SP) and 7 (Fuzzy PD7-SP) membership functions. With advantages of Smith Predictor and Fuzzy Logic Controller the purposed control structure is found better compared with conventional PID controller with Smith Predictor for controlling glycerin bleaching temperature.

Self Tuning Fuzzy Logic controller with Smith structure for controlling glycerin bleaching temperature

Controlling process with lag is not an easy task. The lag can easily cause oscillation that lead to instability of the controller response. The conventional method of controlling this kind of system is not capable of giving satisfactory result. Many delay compensator and predictor methods are introduced to handle system with lag and one of the popular methods is a Smith Predictor. The problem with model base control structure is the mismatch or inaccurate model used as a predictor. This work introduced a Self Tuning Fuzzy Logic controller as an alternative method to solve a process with mismatch delays problem. With advantages of Smith Predictor and Self Tuning Fuzzy Logic Controller the purpose control structure is found giving better performance compare with conventional Fuzzy Logic controller with Smith Predictor Structure.

Modeling of submerged membrane bioreactor filtration process using NARX-ANFIS model

This paper presents modeling techniques for submerged membrane bioreactor (SMBR) filtration process using. The Nonlinear Auto Regressive with Exogenous Input (NARX) structure was used with adaptive neuro-fuzzy interface system (ANFIS) and feed forward neural network (FFNN) are employed to model the filtration system. The transmembrane pressure and the permeate flux were model during the relaxation and permeate cycle. In this work diluted palm oil mill effluent (POME) will be used as an influent of the treatment process. The performance of the models was measured using the R2, mean square error (MSE) and mean absolute deviation (MAD). The result showed that the ANFIS with NARX structure perform slightly better compare with ANN with NARX structure.

PID control structure for glycerin bleaching process: A comparative study

This paper is to investigate the best PID control structure for controlling the glycerin bleaching process that would improve the bleached glycerin quality. An ideal and alternative PID control structures is analyzed. The controller parameters are adjusted based on Wangs tuning method and compared to Ziegler-Nichols method. The system performance is evaluated in terms of settling time and percent overshoot. The results showed that the glycerin bleaching process control can best achieve using alternative PID control structure with Ziegler-Nichols tuning.

Fuzzy Logic controller for glycerin bleaching temperature control

Controlling a process with significant lag is always a challenge task. The response is slow and can cause instability of the controller. In this work the Fuzzy Logic controller is purposed to control the heating stage for glycerin bleaching process. The Fuzzy PD and Fuzzy PI controllers are designed with different sets of membership function and rules. 3, 5 and 7 membership functions with 9, 25 and 49 rules are compared and evaluated to find the suitable set for this application. It was found that the implementation of Fuzzy Logic controller with 25 rules is sufficient to give good control for glycerin bleaching heating process.