Nonlinear System Identification for Aqueous PVA Degradation in a Continuous UV/H2O2 Tubular Photoreactor

Lin, Yi; Dhib, Ramdhane; Mehrvar, Mehrab

doi:10.1021/acs.iecr.0c04637

Cited by 5 publications

(4 citation statements)

References 35 publications

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“…Since the kinetics of the photochemical reactions is non-linear, the process dynamics measured by effluent pH are therefore non-linear. However, the degrees of nonlinearity is still unknown, and it was explored in a previous study (Lin et al, 2021). Thus, the process inputoutput dataset is first fitted with a linear ARX model to evaluate the possibility of low nonlinearity in the process output.…”

Section: Linear Arxmentioning

confidence: 99%

ARX and NARX Modeling and Control of a Continuous UV/H2O2 Photoreactor for the Aqueous PVA Degradation

Lin

2024

Preprint

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Water-soluble polymers are commonly employed as additives in many manufacturing industries, raising the need to treat sewage contaminated with water-soluble polymers to prevent persistent pollutants from entering our environment. The advanced oxidation process (AOP) UV/H2O2 is great at non-selectively degrading organic, polymeric compounds. However, most of the available information came from our research group, and there exist many gaps in other previous studies. The first part of this study presents a comprehensive literature review, modeling, and development of a control strategy of the UV/H2O2 process in degrading water- soluble polyvinyl alcohol (PVA), a commonly used polymeric additive. The second part comprises the dynamic modeling using UV/H2O2 photoreactor identification. The input-output model development was performed using the linear AutoRegressive with eXogenous input (ARX), non-linear ARX (NARX), and Hammerstein-Wiener techniques sigmoid-network-based NARX produced the best representation of the process dynamics. The design of PID controllers tuned using ARX and sigmoid-network-based NARX models is discussed, and the controller performance is analyzed for set-point tracking and disturbance rejection. The closed-loop response of ARX-PID and NARX-PID are deemed adequate. The NARX-PID seems more suitable for the studied process, whereas the ARX-PID has lower IAE and produces a more aggressive controlled output response, but it is robust in disturbance rejection. Thus, ARX-PID is adequate for frequent process disturbances but less for process set-point tracking.

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Section: Linear Arxmentioning

confidence: 99%

ARX and NARX Modeling and Control of a Continuous UV/H2O2 Photoreactor for the Aqueous PVA Degradation

Lin

2024

Preprint

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“…The parameters of each dynamic structure, illustrated in Figure 5, are estimated based on the basic mathematical equation presented earlier. Describing each modelling structure is out of the scope of this study and has been discussed in our previous study [36,37]. Figure 6 illustrates the necessary steps prior to, during, and after the system identification.…”

Section: System Identification/modellingmentioning

confidence: 99%

“…It was observed that ARX-PID and ARX-sigmoid-PID have the best performance of all. However, the response of the NARX-sigmoid-PID was sluggish, and the ARX-PID had a considerable overshoot [36,37,75].…”

Section: Controlling Aop-based Treatment Processesmentioning

confidence: 99%

Dynamic Modelling, Process Control, and Monitoring of Selected Biological and Advanced Oxidation Processes for Wastewater Treatment: A Review of Recent Developments

Parsa,

Dhib,

Mehrvar

2024

Bioengineering

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This review emphasizes the significance of formulating control strategies for biological and advanced oxidation process (AOP)-based wastewater treatment systems. The aim is to guarantee that the effluent quality continuously aligns with environmental regulations while operating costs are minimized. It highlights the significance of understanding the dynamic behaviour of the process in developing effective control schemes. The most common process control strategies in wastewater treatment plants (WWTPs) are explained and listed. It is emphasized that the proper control scheme should be selected based on the process dynamic behaviour and control goal. This study further discusses the challenges associated with the control of wastewater treatment processes, including inadequacies in developed models, the limitations of most control strategies to the simulation stage, the imperative requirement for real-time data, and the financial and technical intricacies associated with implementing advanced controller hardware. It is discussed that the necessity of the availability of real-time data to achieve reliable control can be achieved by implementing proper, accurate hardware sensors in suitable locations of the process or by developing and implementing soft sensors. This study recommends further investigation on available actuators and the criteria for choosing the most appropriate one to achieve robust and reliable control in WWTPs, especially for biological and AOP-based treatment approaches.

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“…Though used as a leading method for degradation of organic pollutants, biological treatment can only treat wastewater that is readily degradable by living organisms. If that is not possible, researchers mainly focused on the oxidation of polyvinyl alcohol (PVA) in an Advanced Oxidation Process (AOP) such as UV/H2O2 process as an easy process owing to its relatively developed kinetics, non-selective degradation, low cost, and ease in operation at large-scale [1][2][3]. In particular, the UV/H2O2 process requires modelling to establish a control system that prevents adverse effects of PVA and residual hydrogen peroxide (H2O2) to the aquatic system and subsequent biological processes by maintaining H2O2 residuals in the treated effluent within a safe level.…”

mentioning

confidence: 99%

ARX-PID/NARX-PID Modelling and Control of UV/H2O2 Tubular Photoreactor for PVA Degradation in Water

Lin¹,

Mehrvar²,

Dhib³

2021

International Conference of Recent Trends in Environmental Science and Engineering

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Various industries rely on water-soluble polymers as additives, therefore, it is imperative to treat them so that they do not enter our environment as persistent pollutants. Though used as a leading method for degradation of organic pollutants, biological treatment can only treat wastewater that is readily degradable by living organisms. If that is not possible, researchers mainly focused on the oxidation of polyvinyl alcohol (PVA) in an Advanced Oxidation Process (AOP) such as UV/H2O2 process as an easy process owing to its relatively developed kinetics, non-selective degradation, low cost, and ease in operation at large-scale [1][2][3]. In particular, the UV/H2O2 process requires modelling to establish a control system that prevents adverse effects of PVA and residual hydrogen peroxide (H2O2) to the aquatic system and subsequent biological processes by maintaining H2O2 residuals in the treated effluent within a safe level. During this study, the performance of black-box methods was examined in determining the dynamics of polyvinyl alcohol degradation in various UV/H2O2 systems, where process inputs and responses involved hydrogen peroxide concentration and acidity, respectively. The complete data analysis and model fitting is undertaken with MATLAB R2019b software. Models including the linear AutoRegressive with eXogenous Input (ARX), the nonlinear ARX (NARX), and the Hammerstein-Wiener model are compared for their success in providing an accurate representation of statistical dynamics. Comparatively, the sigmoidnetwork-based NARX was better at representing the process dynamics when compared to others. The study also explores the design of PID controllers via ARX and sigmoid-network-based NARX models and analyzes controller performance for set-point tracking and disturbance rejection. The ARX-P, ARX-PI, NARX-P, and NARX-PI controllers were not adequate for a good control design as they exhibit higher offset from set-point, higher overshoot, and longer settling time. The ARX-PID and NARX-PID provide adequate closed-loop responses, while NARX-PID seems better suited for the studied process. However, the ARX-PID has a higher IAE and produces a more robust output response against disturbances as it is adequate for processing disturbances but less useful in tracking process set-points. As a result, to compensate for the complexity in generating models and tuning the parameters with the NARX model, an approximation based on the ARX model is appropriate when its implementation will be followed by another set-up for H2O2 elimination. Although feasibility of linear control scheme was presented, it is suggested that similar scenarios should be considered in future designs, validations, and performance evaluations of the entire controlled system, especially for improving controller robustness by implementing multivariate adaptive controls and linear or non-linear predictive controls [4][5][6][7][8][9].

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Nonlinear System Identification for Aqueous PVA Degradation in a Continuous UV/H₂O₂ Tubular Photoreactor

Cited by 5 publications

References 35 publications

ARX and NARX Modeling and Control of a Continuous UV/H2O2 Photoreactor for the Aqueous PVA Degradation

ARX and NARX Modeling and Control of a Continuous UV/H2O2 Photoreactor for the Aqueous PVA Degradation

Dynamic Modelling, Process Control, and Monitoring of Selected Biological and Advanced Oxidation Processes for Wastewater Treatment: A Review of Recent Developments

ARX-PID/NARX-PID Modelling and Control of UV/H2O2 Tubular Photoreactor for PVA Degradation in Water

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