Pornsiri Kaewpradit | Prince of Songkla University (original) (raw)

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Papers by Pornsiri Kaewpradit

Chemical Engineering Science, 2008

Songklanakarin Journal of Science and Technology (SJST), 2013

Ammonia (NH3) is a noxious gas that can cause serious damage to human health and to the environme... more Ammonia (NH3) is a noxious gas that can cause serious damage to human health and to the environment. Thus, elimination of NH3 in waste air by treating before releasing to the atmosphere is necessary. In this study, titanium dioxide (TiO2) nanoparticle Degussa P25 coating on glass cylindrical tube supporters was synthesized and used as photocatalytic in a continuous photoreactor device. UV light source was vertically installed around the photoreactor in a stainless steel chamber. Experiments were designed and conducted based on central composite design (CCD) and analyzed using response surface methodology (RSM). This RSM was used to evaluate the effects of process variables and their interactions towards attainment of their optimum conditions. Three significant variables, light intensity (23-114W/m2), waste air flow rate (1-5 l/min), and TiO2 loading (1.18-5.90 g) were fitted in a quadratic model to the response of NH3 treatment efficiency. R2 of 0.9783 wassatisfactorily evaluated fo...

ABSTRACT Thesis (M.Eng)--Chulalongkorn University, 2002 Process measurements are taken in chemica... more ABSTRACT Thesis (M.Eng)--Chulalongkorn University, 2002 Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. Thus, data reconciliation is frequently required before the data can be used for evaluating process control or process performance. In this research, the benefits of combining linear dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example problems, a steel pickling process and an exothermic batch reactor. The robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The results show thata rudimentary treatment of measurement errors and an estimation of unknown quantities have proved extremely effective. Therefore, DDR approach is an important adjunct to advanced control. การควบคุมและการศึกษาพฤติกรรมของกระบวนการในโรงงานอุตสาหกรรมเคมีนั้นต้องอาศัยเครื่องมือวัดเพื่อให้ได้มาซึ่งข้อมูลของระบบที่ต้องการ แต่เนื่องจากข้อจำกัดในด้านเทคนิคหรือต้นทุน ข้อมูลของระบบโดยทั่วไปไม่สามารถวัดหรือทราบค่าที่แน่นอนได้ อีกทั้งความผิดพลาดของเครื่องมือวัดก็เป็นอีกปัจจัยหนึ่งที่ทำให้ข้อมูลวัดของระบบไม่ถูกต้อง ดังนั้นการปรับให้สอดคล้องของข้อมูลจึงเป็นขั้นตอนที่สำคัญมากขั้นตอนหนึ่ง ก่อนที่ข้อมูลวัดจะถูกนำไปใช้ในการควบคุมหรือทำนาย พฤติกรรมของระบบ งานวิจัยนี้มุ่งเน้นให้เห็นถึงประโยชน์ของการประยุกต์ใช้ตัวควบคุมแบบเจเนอริกโมเดล (GMC) ร่วมกับการปรับให้สอดคล้องของข้อมูลแบบพลวัต (DDR) เพื่อควบคุมตัวแปรสเตทของกระบวนการกำจัดสนิมเหล็กและถังปฏิกรณ์คายความร้อนแบบกะให้มีค่าที่ต้องการ ซึ่งวิธีควบคุมดังกล่าวถูกทดสอบความทนทานทั้งในกรณีของแบบจำลองและตัวแปรผิดพลาด และในกรณีที่ระบบถูกรบกวนด้วยตัวแปรรบกวน ผลการทดสอบทั้งในกรณีการควบคุมตัวแปรสเตทให้เข้าสู่ค่าเป้าหมาย (Set point regulation) และการเปลี่ยนแปลงค่าเป้าหมาย (Set point tracking) แสดงให้เห็นถึงประสิทธิภาพของการปรับให้สอดคล้องของข้อมูลในการกำจัดความผิดพลาดจากการวัด และในการประมาณค่าตัวแปรระบบที่ไม่ทราบค่า ดังนั้นจึงอาจกล่าวได้ว่าขั้นตอนการปรับให้สอดคล้องของข้อมูล (DDR approach)เป็นขั้นตอนหนึ่งที่สำคัญในกระบวนการควบคุมชั้นสูง

Songklanakarin Journal of Science and Technology, 2013

Ammonia (NH 3 ) is a noxious gas that can cause serious damage to human health and to the environ... more Ammonia (NH 3 ) is a noxious gas that can cause serious damage to human health and to the environment. Thus, elimination of NH 3 in waste air by treating before releasing to the atmosphere is necessary. In this study, titanium dioxide (TiO 2 ) nanoparticle Degussa P25 coating on glass cylindrical tube supporters was synthesized and used as photocatalytic in a continuous photoreactor device. UV light source was vertically installed around the photoreactor in a stainless steel chamber. Experiments were designed and conducted based on central composite design (CCD) and analyzed using response surface methodology (RSM). This RSM was used to evaluate the effects of process variables and their interactions towards attainment of their optimum conditions. Three significant variables, light intensity (23-114W/m 2 ), waste air flow rate (1-5 l/min), and TiO 2 loading (1.18-5.90 g) were fitted in a quadratic model to the response of NH 3 treatment efficiency. R 2 of 0.9783 was satisfactorily e...

Processes

The deodorization of the refined palm oil process is simulated here using ASPEN HYSYS. In the abs... more The deodorization of the refined palm oil process is simulated here using ASPEN HYSYS. In the absence of a library molecular distillation (MD) process in ASPEN HYSYS, first, a single flash vessel is considered to represent a falling film MD process which is simulated for a binary system taken from the literature and the model predictions are compared with the published work based on ASPEN PLUS and DISMOL. Second, the developed MD process is extended to simulate the deodorization process. Parameter estimation technique is used to estimate the Antoine's parameters based on literature data to calculate the pure component vapor pressure. The model predictions are then validated against the patented results of refining edible oil rich in natural carotenes and vitamin E and simulation results were found to be in good agreement, within a ±2% error of the patented results. Third, Response Surface Methodology (RSM) is employed to develop non-linear second-order polynomial equations based model for the deodorization process and the effects of various operating parameters on the performance of the process are studied. Finally, an optimization framework is developed to maximize the concentration of beta-carotene, tocopherol and free fatty acid while optimizing the feed flow rate, temperature and pressure subject to process constrains. The optimum results of feed flow rate, temperature, and pressure were determined as 1291 kg/h, 147 • C and 0.0007 kPa respectively, and the concentration responses of beta-carotene, tocopherol and free fatty acid were found to be 0.000575, 0.000937 and 0.999840 respectively.

A Kalman filter (KF) estimator has been formulated using a sequence of reduced-order models repre... more A Kalman filter (KF) estimator has been formulated using a sequence of reduced-order models representing a whole batch behavior for providing the estimates of dynamic composition in a ternary batch distillation process operated in an optimal-reflux policy. A set of full-order models is firstly obtained by linearizing around different pseudo-steady state operating conditions along batch optimal profiles. They are further reduced their orders to achieve their observability and controllability individually by using a model reduction method. The performances of the reduced-estimator have been investigated and compared with those of a conventional nonlinear estimator. Simulation results have demonstrated that the performances of the proposed estimator are reasonably good and almost identical to the conventional one in all cases.

Thesis (M.Eng)--Chulalongkorn University, 2002 Process measurements are taken in chemical plants ... more Thesis (M.Eng)--Chulalongkorn University, 2002 Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. Thus, data reconciliation is frequently required before the data can be used for evaluating process control or process performance. In this research, the benefits of combining linear dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example problems, a steel pickling process and an exothermic batch reactor. The robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The res...

Several chemical industrial plants such as electroplating and metal finishing plants have used st... more Several chemical industrial plants such as electroplating and metal finishing plants have used strong acids and strong bases in production lines. These acids and bases are then released from the production lines to a wastewater treatment system and then treated to achieve compliance with an effluent standard. It is well known that the pH control of a wastewater treatment process is one of the most challenging control problems due to high non-linearity and time-variance of the pH value during pH titration. A conventional PID controller and an on-off controller are rarely able to handle this non- linearity resulting in poor control performances. Therefore, advanced nonlinear control techniques are needed. This research presents simulation study of Globally Linearizing Control (GLC) together with an extended Kalman Filter to control pH of the wastewater treatment process of an electroplating plant. The GLC, one of the advanced nonlinear model-based control techniques, has been develope...

Proceedings of the 14th Asia Pacific Confederation of Chemical Engineering Congress, 2012

Korean Journal of Chemical Engineering, 2003

To implement an advanced control algorithm, measurements of process outputs are usually used to d... more To implement an advanced control algorithm, measurements of process outputs are usually used to determine control action to a process. Nevertheless, measurements of process outputs are often subjected to measuring and signal errors as well as noise. Therefore, in this work, Generic Model Control (GMC), an advanced control technique, with data reconciliation technique has been applied to control the pH of the pickling process consisting of three pickling and three rinsing baths. Here, the data reconciliation problem involves six nodes and fourteen streams. The presence of errors in the data set is determined and identified via measurement test. In addition, the measurement error covariance is initially assumed to be a known variance matrix and is updated every iteration. Simulation results have shown that the reconciled process data give a better view of the true states of the process than raw measuring data. With these reconciled process data, the GMC controller can control the process at a desired set point with great success.

Chemical Engineering Science, 2008

A novel Kalman estimator has been proposed to provide the estimates of dynamic composition in a t... more A novel Kalman estimator has been proposed to provide the estimates of dynamic composition in a ternary batch distillation process operated in an optimal-reflux policy. The estimator is formulated based on a sequence of reduced-order process models representing a whole batch behavior. Therefore, the full-order models are first developed around different pseudo-steady-state operating conditions along batch optimal profiles. Then they reduce their orders to achieve all state observability and controllability by a balanced truncation method. In the estimator scheme, the reduced models as well as relevant covariance matrices of process noise are pre-scheduled and switched according to any desired periods. Four important issues have been studied including selection of a sensor frequency, effects of an integrating step size, a state initialization and a measurement noise. The performances of the reduced estimator have been investigated and compared with those of a conventional nonlinear estimator. Simulation results have demonstrated that the performances of the novel linear estimator are reasonably good and almost identical to the nonlinear estimator in all cases, though the linear estimator performs rather sensitively to the effect of high measurement noise. Nevertheless, it has been found to be applicable to implement in real plants with much lower computation effort, easier state initialization and unrequired a priori knowledge of thermodynamics.

A Kalman filter (KF) estimator has been formulated using a sequence of reduced-order models repre... more A Kalman filter (KF) estimator has been formulated using a sequence of reduced-order models representing a whole batch behavior for providing the estimates of dynamic composition in a ternary batch distillation process operated in an optimal-reflux policy. A set of full-order models is firstly obtained by linearizing around different pseudo-steady state operating conditions along batch optimal profiles. They are further reduced their orders to achieve their observability and controllability individually by using a model reduction method. The performances of the reduced-estimator have been investigated and compared with those of a conventional nonlinear estimator. Simulation results have demonstrated that the performances of the proposed estimator are reasonably good and almost identical to the conventional one in all cases.

Chemical Engineering Science, 2008

Songklanakarin Journal of Science and Technology (SJST), 2013

Ammonia (NH3) is a noxious gas that can cause serious damage to human health and to the environme... more Ammonia (NH3) is a noxious gas that can cause serious damage to human health and to the environment. Thus, elimination of NH3 in waste air by treating before releasing to the atmosphere is necessary. In this study, titanium dioxide (TiO2) nanoparticle Degussa P25 coating on glass cylindrical tube supporters was synthesized and used as photocatalytic in a continuous photoreactor device. UV light source was vertically installed around the photoreactor in a stainless steel chamber. Experiments were designed and conducted based on central composite design (CCD) and analyzed using response surface methodology (RSM). This RSM was used to evaluate the effects of process variables and their interactions towards attainment of their optimum conditions. Three significant variables, light intensity (23-114W/m2), waste air flow rate (1-5 l/min), and TiO2 loading (1.18-5.90 g) were fitted in a quadratic model to the response of NH3 treatment efficiency. R2 of 0.9783 wassatisfactorily evaluated fo...

ABSTRACT Thesis (M.Eng)--Chulalongkorn University, 2002 Process measurements are taken in chemica... more ABSTRACT Thesis (M.Eng)--Chulalongkorn University, 2002 Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. Thus, data reconciliation is frequently required before the data can be used for evaluating process control or process performance. In this research, the benefits of combining linear dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example problems, a steel pickling process and an exothermic batch reactor. The robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The results show thata rudimentary treatment of measurement errors and an estimation of unknown quantities have proved extremely effective. Therefore, DDR approach is an important adjunct to advanced control. การควบคุมและการศึกษาพฤติกรรมของกระบวนการในโรงงานอุตสาหกรรมเคมีนั้นต้องอาศัยเครื่องมือวัดเพื่อให้ได้มาซึ่งข้อมูลของระบบที่ต้องการ แต่เนื่องจากข้อจำกัดในด้านเทคนิคหรือต้นทุน ข้อมูลของระบบโดยทั่วไปไม่สามารถวัดหรือทราบค่าที่แน่นอนได้ อีกทั้งความผิดพลาดของเครื่องมือวัดก็เป็นอีกปัจจัยหนึ่งที่ทำให้ข้อมูลวัดของระบบไม่ถูกต้อง ดังนั้นการปรับให้สอดคล้องของข้อมูลจึงเป็นขั้นตอนที่สำคัญมากขั้นตอนหนึ่ง ก่อนที่ข้อมูลวัดจะถูกนำไปใช้ในการควบคุมหรือทำนาย พฤติกรรมของระบบ งานวิจัยนี้มุ่งเน้นให้เห็นถึงประโยชน์ของการประยุกต์ใช้ตัวควบคุมแบบเจเนอริกโมเดล (GMC) ร่วมกับการปรับให้สอดคล้องของข้อมูลแบบพลวัต (DDR) เพื่อควบคุมตัวแปรสเตทของกระบวนการกำจัดสนิมเหล็กและถังปฏิกรณ์คายความร้อนแบบกะให้มีค่าที่ต้องการ ซึ่งวิธีควบคุมดังกล่าวถูกทดสอบความทนทานทั้งในกรณีของแบบจำลองและตัวแปรผิดพลาด และในกรณีที่ระบบถูกรบกวนด้วยตัวแปรรบกวน ผลการทดสอบทั้งในกรณีการควบคุมตัวแปรสเตทให้เข้าสู่ค่าเป้าหมาย (Set point regulation) และการเปลี่ยนแปลงค่าเป้าหมาย (Set point tracking) แสดงให้เห็นถึงประสิทธิภาพของการปรับให้สอดคล้องของข้อมูลในการกำจัดความผิดพลาดจากการวัด และในการประมาณค่าตัวแปรระบบที่ไม่ทราบค่า ดังนั้นจึงอาจกล่าวได้ว่าขั้นตอนการปรับให้สอดคล้องของข้อมูล (DDR approach)เป็นขั้นตอนหนึ่งที่สำคัญในกระบวนการควบคุมชั้นสูง

Songklanakarin Journal of Science and Technology, 2013

Ammonia (NH 3 ) is a noxious gas that can cause serious damage to human health and to the environ... more Ammonia (NH 3 ) is a noxious gas that can cause serious damage to human health and to the environment. Thus, elimination of NH 3 in waste air by treating before releasing to the atmosphere is necessary. In this study, titanium dioxide (TiO 2 ) nanoparticle Degussa P25 coating on glass cylindrical tube supporters was synthesized and used as photocatalytic in a continuous photoreactor device. UV light source was vertically installed around the photoreactor in a stainless steel chamber. Experiments were designed and conducted based on central composite design (CCD) and analyzed using response surface methodology (RSM). This RSM was used to evaluate the effects of process variables and their interactions towards attainment of their optimum conditions. Three significant variables, light intensity (23-114W/m 2 ), waste air flow rate (1-5 l/min), and TiO 2 loading (1.18-5.90 g) were fitted in a quadratic model to the response of NH 3 treatment efficiency. R 2 of 0.9783 was satisfactorily e...

Processes

The deodorization of the refined palm oil process is simulated here using ASPEN HYSYS. In the abs... more The deodorization of the refined palm oil process is simulated here using ASPEN HYSYS. In the absence of a library molecular distillation (MD) process in ASPEN HYSYS, first, a single flash vessel is considered to represent a falling film MD process which is simulated for a binary system taken from the literature and the model predictions are compared with the published work based on ASPEN PLUS and DISMOL. Second, the developed MD process is extended to simulate the deodorization process. Parameter estimation technique is used to estimate the Antoine's parameters based on literature data to calculate the pure component vapor pressure. The model predictions are then validated against the patented results of refining edible oil rich in natural carotenes and vitamin E and simulation results were found to be in good agreement, within a ±2% error of the patented results. Third, Response Surface Methodology (RSM) is employed to develop non-linear second-order polynomial equations based model for the deodorization process and the effects of various operating parameters on the performance of the process are studied. Finally, an optimization framework is developed to maximize the concentration of beta-carotene, tocopherol and free fatty acid while optimizing the feed flow rate, temperature and pressure subject to process constrains. The optimum results of feed flow rate, temperature, and pressure were determined as 1291 kg/h, 147 • C and 0.0007 kPa respectively, and the concentration responses of beta-carotene, tocopherol and free fatty acid were found to be 0.000575, 0.000937 and 0.999840 respectively.

A Kalman filter (KF) estimator has been formulated using a sequence of reduced-order models repre... more A Kalman filter (KF) estimator has been formulated using a sequence of reduced-order models representing a whole batch behavior for providing the estimates of dynamic composition in a ternary batch distillation process operated in an optimal-reflux policy. A set of full-order models is firstly obtained by linearizing around different pseudo-steady state operating conditions along batch optimal profiles. They are further reduced their orders to achieve their observability and controllability individually by using a model reduction method. The performances of the reduced-estimator have been investigated and compared with those of a conventional nonlinear estimator. Simulation results have demonstrated that the performances of the proposed estimator are reasonably good and almost identical to the conventional one in all cases.

Thesis (M.Eng)--Chulalongkorn University, 2002 Process measurements are taken in chemical plants ... more Thesis (M.Eng)--Chulalongkorn University, 2002 Process measurements are taken in chemical plants for the purpose of evaluating process control or process performance. However, not all variables needed are generally measured due to technical infeasibility or cost. Furthermore, the measurements are often contaminated in the sense that random noise may be present due to result of miscalibration or failure of the measuring instruments. Thus, data reconciliation is frequently required before the data can be used for evaluating process control or process performance. In this research, the benefits of combining linear dynamic data reconciliation (DDR) with Generic Model Control (GMC) are demonstrated on two example problems, a steel pickling process and an exothermic batch reactor. The robustness of the proposed control strategy is investigated with respect to changes in process condition, modeling error and disturbance variable for both set point regulation and set point tracking. The res...

Several chemical industrial plants such as electroplating and metal finishing plants have used st... more Several chemical industrial plants such as electroplating and metal finishing plants have used strong acids and strong bases in production lines. These acids and bases are then released from the production lines to a wastewater treatment system and then treated to achieve compliance with an effluent standard. It is well known that the pH control of a wastewater treatment process is one of the most challenging control problems due to high non-linearity and time-variance of the pH value during pH titration. A conventional PID controller and an on-off controller are rarely able to handle this non- linearity resulting in poor control performances. Therefore, advanced nonlinear control techniques are needed. This research presents simulation study of Globally Linearizing Control (GLC) together with an extended Kalman Filter to control pH of the wastewater treatment process of an electroplating plant. The GLC, one of the advanced nonlinear model-based control techniques, has been develope...

Proceedings of the 14th Asia Pacific Confederation of Chemical Engineering Congress, 2012

Korean Journal of Chemical Engineering, 2003

To implement an advanced control algorithm, measurements of process outputs are usually used to d... more To implement an advanced control algorithm, measurements of process outputs are usually used to determine control action to a process. Nevertheless, measurements of process outputs are often subjected to measuring and signal errors as well as noise. Therefore, in this work, Generic Model Control (GMC), an advanced control technique, with data reconciliation technique has been applied to control the pH of the pickling process consisting of three pickling and three rinsing baths. Here, the data reconciliation problem involves six nodes and fourteen streams. The presence of errors in the data set is determined and identified via measurement test. In addition, the measurement error covariance is initially assumed to be a known variance matrix and is updated every iteration. Simulation results have shown that the reconciled process data give a better view of the true states of the process than raw measuring data. With these reconciled process data, the GMC controller can control the process at a desired set point with great success.

Chemical Engineering Science, 2008

A novel Kalman estimator has been proposed to provide the estimates of dynamic composition in a t... more A novel Kalman estimator has been proposed to provide the estimates of dynamic composition in a ternary batch distillation process operated in an optimal-reflux policy. The estimator is formulated based on a sequence of reduced-order process models representing a whole batch behavior. Therefore, the full-order models are first developed around different pseudo-steady-state operating conditions along batch optimal profiles. Then they reduce their orders to achieve all state observability and controllability by a balanced truncation method. In the estimator scheme, the reduced models as well as relevant covariance matrices of process noise are pre-scheduled and switched according to any desired periods. Four important issues have been studied including selection of a sensor frequency, effects of an integrating step size, a state initialization and a measurement noise. The performances of the reduced estimator have been investigated and compared with those of a conventional nonlinear estimator. Simulation results have demonstrated that the performances of the novel linear estimator are reasonably good and almost identical to the nonlinear estimator in all cases, though the linear estimator performs rather sensitively to the effect of high measurement noise. Nevertheless, it has been found to be applicable to implement in real plants with much lower computation effort, easier state initialization and unrequired a priori knowledge of thermodynamics.

A Kalman filter (KF) estimator has been formulated using a sequence of reduced-order models repre... more A Kalman filter (KF) estimator has been formulated using a sequence of reduced-order models representing a whole batch behavior for providing the estimates of dynamic composition in a ternary batch distillation process operated in an optimal-reflux policy. A set of full-order models is firstly obtained by linearizing around different pseudo-steady state operating conditions along batch optimal profiles. They are further reduced their orders to achieve their observability and controllability individually by using a model reduction method. The performances of the reduced-estimator have been investigated and compared with those of a conventional nonlinear estimator. Simulation results have demonstrated that the performances of the proposed estimator are reasonably good and almost identical to the conventional one in all cases.