Application of response surface methodology as a new PID tuning method in an electrocoagulation process control case

Camcıoğlu, Şule; Özyurt, Baran; Doğan, İzzet; Hapoğlu, Hale

doi:10.2166/wst.2017.506

Cited by 10 publications

(6 citation statements)

References 26 publications

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“…Recently, the application of surrogates has been considered to reduce computational efforts in different engineering design and control problems. 45,46 Such main surrogates used in deterministic and stochastic PID tuning are polynomial regression (also called response surface methodology), [47][48][49] Radial Basis Function (RBF), [50][51][52] and Kriging surrogate. 4,[53][54][55] To the best of our knowledge, there is a lack of studies that consider the effect of uncertainty in physical load parameters on the optimal design of controllers with the lower computational cost (lower number of simulation experiments).…”

Section: Related Workmentioning

confidence: 99%

Robust tuning and sensitivity analysis of stochastic integer andfractional‐order PIDcontrol systems: application ofsurrogate‐basedrobustsimulation‐optimization

Parnianifard

Fakhfakh

Kotti

et al. 2020

Int J Numerical Modelling

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This paper aims to make a trade‐off between performance and robustness in stochastic control systems with probabilistic uncertainties. For this purpose, we develop a surrogate‐based robust simulation‐optimization approach for robust tuning and analyzing the sensitivity of stochastic controllers. Kriging surrogate is combined with robust design optimization to construct a robust simulation‐optimization model in the class of dual response surfaces. Randomness in simulation experiments due to uncertainty is analyzed through bootstrapping technique by computing confidence regions for the estimation of Pareto frontier. Results confirmed a proper trade‐off between the model's performance with the measure of expected Integral Squared Error (ISE) and robustness against uncertainty in the plant's physical parameters. Finally, the proposed method is evaluated in terms of accuracy, computational cost, and simplicity particularly in comparison with some common existed techniques in the tuning of the Proportional‐Integral‐Derivative (PID) and Fractional‐Order PID (FOPID) controllers.

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Section: Related Workmentioning

confidence: 99%

Robust tuning and sensitivity analysis of stochastic integer andfractional‐order PIDcontrol systems: application ofsurrogate‐basedrobustsimulation‐optimization

Parnianifard

Fakhfakh

Kotti

et al. 2020

Int J Numerical Modelling

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“…RSM has been applied to optimize PID controller parameters for the pH and electrical conductivity values of a batch electrocoagulation process in which pulp and paper mill wastewater was treated, and to investigate the effects of control action on pollutant removal and energy consumption. ISE, IAE, ITAE and ITSE values are selected as responses which indicators of controller performance [10]. Control of the absorption column was carried out using a PID controller with the affluent water flow to the column corresponding to the manipulated variable and the component (CO2) concentration in the gas stream effluent to the column corresponding to the controlled variable.…”

Section: Introductionmentioning

confidence: 99%

Determination of optimal PID control parameters by response surface methodology

Aldemır

Anwer

2020

International Advanced Researches and Engineering Journal

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Proportional-Integral-Derivative (PID) controllers are the most widely used systems in industrial applications and in academic research regarding control engineering. In this study, the optimal PID control parameters of a liquid level control system were determined with Response Surface Methodology. Dynamic analysis was carried out on the liquid level control system to prepare the reaction curve. Accordingly, dead time, time constant and process gain values were determined as 16s, 261s and 0.842, respectively. Based on the dynamic analysis, PID parameters were calculated in accordance with the Cohen-Coon, Ziegler-Nichols, Yuwana-Seborg methods, which are the commonly used tuning methods. The Kp, τI, τD parameters were calculated as 30.77, 29.15 and 5.4 with the Cohen-Coon method, as 0.453, 30.0 and 7.5 with the Ziegler-Nichols method and as 1.63, 686.3 and 117.7 with the Yuwana-Seborg method, respectively. The PID control parameters applied for the 40cm, 50cm and 60cm set points and ISE and IAE control performance values after experiments were calculated. The Kp, τI and τD values were selected as the independent parameters, while the ISE and IAE values were chosen as the dependent variables. The numerical values of the responses for the runs in the design matrices were determined with a closed-loop PID controller with the liquid level system block diagram that was designed in MATLAB/Simulink. The simulations proposed by the trial version of Design Expert 7.0 program were performed in order and the IAE and ISE values were calculated after the simulations were processed. In this study, minimum ISE and IAE values were selected to determine the best PID parameters of a liquid level control system. The optimal PID control parameters of the liquid level system required to obtain the lowest ISE and IAE values were determined as 23.14, 28.31 and 11.50 for Kp, τI and τD, respectively.

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“…In the water treatment by electrocoagulation, thus, the determination of the contaminant isotherm on the Aluminum electrode used is reported for Boron removal, considering that Faraday's Law corresponds to Langmuir's isotherm model [16]. Also, computer-aided modeling has been implemented using Response Surface Methodology (RSM) [17][18]. Thus, the objective of the present study was to design and evaluate the performance of a laboratory-scale electrocoagulation cell in greywater treatment, optimizing its operation by making changes in the electrode material, the distance between them, and the current supplied.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Parameters in the Removal of Linear Alkylbenzene Sulfonate Anionic Surfactant Using Electrocoagulation

Villabona-Ortíz

De-La-Rosa-Jiménez

2020

Rev. Fac. Ing.

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The objective of the present investigation was to construct an electrocoagulation cell in a batch system and to evaluate its capacity to remove the anionic surfactant of the linear alkylbenzene sulfonate (LAS), which is present in gray water determining the effect of the type of electrodes (Al or Fe), distance between electrodes (1, 1.5 and 2 cm) and voltages (10, 15 and 20 V). The experimental tests were carried out for 20 min. The dimensions of the short wave electrolysis cell built in glass were 26 cm long, 7 cm wide and 12 cm high, with 10 electrodes of 12x6 cm supported by a PVC structure. The concentration of LAS in the solution was determined by employing UV-Vis spectrometry applying the Methylene Blue Active Substances (MBAS) method. A higher removal of 65.55% was obtained when aluminum electrodes were used, and 69.11% with iron electrodes a separation of 1.5 cm and a voltage of 20 V, presenting less change in pH, conductivity, and energy consumption when using the Al3 electrode. When evaluating the effect of time at the best experimental configuration (Al, 1.5 cm, 20 V) it was established that the removal efficiency increased to 75.13% in 60 min. Electrocoagulation with aluminum electrodes is presented as an efficient alternative for the removal of LAS in solution.

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Application of response surface methodology as a new PID tuning method in an electrocoagulation process control case

Cited by 10 publications

References 26 publications

Robust tuning and sensitivity analysis of stochastic integer andfractional‐order PIDcontrol systems: application ofsurrogate‐basedrobustsimulation‐optimization

Robust tuning and sensitivity analysis of stochastic integer andfractional‐order PIDcontrol systems: application ofsurrogate‐basedrobustsimulation‐optimization

Determination of optimal PID control parameters by response surface methodology

Evaluation of Parameters in the Removal of Linear Alkylbenzene Sulfonate Anionic Surfactant Using Electrocoagulation

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