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Record W4400237455 · doi:10.11159/rtese24.143

Decoupled PID Controller Design for Multi-Input Multi-Output PVA Degradation Process in a UV/H<sub>2</sub>O<sub>2</sub> Photoreactor

2024· article· en· W4400237455 on OpenAlexaff
Zahra Parsa, Ramdhane Dhib, Mehrab Mehrvar

Bibliographic record

VenueProceedings of the International Conference of Recent Trends in Environmental Science and Engineering · 2024
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDegradation (telecommunications)PID controllerProcess (computing)Control theory (sociology)Process controlController (irrigation)Materials scienceComputer scienceControl engineeringControl (management)EngineeringOperating systemTemperature controlArtificial intelligence

Abstract

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Synthetic water-soluble polymers, exemplified by polyvinyl alcohol (PVA), are widely consumed in diverse industries as raw materials or process-facilitating agents such as coatings, solvents, or lubricants [1,2].However, a substantial portion of these materials ends up in industrial wastewater, resulting in significant challenges in wastewater treatment.The nonbiodegradable nature of these polymers necessitates employing advanced treatment processes, such as advanced oxidation processes (AOPs), to remove them effectively [3].Among AOPs, the UV/H2O2 process has emerged as a promising solution for PVA degradation due to its proven efficiency in experimental studies [4][5][6][7][8].Nonetheless, continuously achieving optimal PVA degradation while ensuring safe residual H2O2 levels in the process effluent remains a critical concern [9][10][11].This study focuses on designing a robust multi-loop proportional-integral-derivative (PID) feedback control specifically tailored for the multi-input multi-output (MIMO) PVA degradation process in a UV/H2O2 photoreactor.This approach is selected due to the prevalence, adaptability, and simplicity of implementing PID controllers in industries, including wastewater treatment plants [12].However, it is crucial to acknowledge that transitioning PID feedback control from a singleinput single-output (SISO) system to a MIMO configuration introduces complexities that require meticulous consideration of process interactions.The significant hurdles in formulating a multi-loop PID feedback control for MIMO systems encompass identifying the interactions among process variables, mitigating these interactions, and selecting optimal manipulated variable/control variable (MV/CV) control pairs [13,14].Relative gain array (RGA) analysis is a valuable tool for navigating these challenges.One effective strategy to address process interactions involves implementing feedforward decouplers, enabling independent control of each CV by manipulating only one MV [15].In this study, the implementation of RGA analysis facilitated the identification of interactions between key process CVs, including the effluent total organic carbon (TOC) and residual H2O2 concentrations (mg/L), and MVs including PVA feed flow rate (mL/min) and inlet H2O2 concentration (mg/L).Feedforward PID controllers, acting as decouplers, were designed and integrated into the closed-loop control system of the process to mitigate the indicated interactions.Subsequently, PID controllers for each decoupled loop were meticulously tuned to ensure effective disturbance rejection on the CV within a closed feedback loop.The tuned controllers can also effectively manipulate the corresponding MV to track the desired setpoint trajectory.Tuning of PID parameters and rigorous simulation studies were conducted using MATLAB Simulink to validate the efficacy of the proposed control strategy.Simulation outcomes underscored the effectiveness of the designed control system, showcasing rapid response and settling times, stability, and minimal overshoot.Furthermore, the practical applicability of the designed control system was examined through realizability analysis assessments of the designed decouplers.The nature of the lag compensator of the designed decouplers serves as evidence of their realizability and feasibility for implementation in real-world applications.Overall, this study and its simulation results demonstrate the effectiveness of the proposed control strategy for PVA degradation in a UV/H2O2 photoreactor.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.262
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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