Multi-centralized control system design based on equivalent transfer functions using gain and phase-margin specifications for unstable TITO process

Besta, Chandra Shekar

doi:10.1007/s40435-017-0345-3

Cited by 5 publications

(5 citation statements)

References 36 publications

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“…Furthermore, the centralized controller can easily be tuned even using the knowledge of the steady-state matrix alone. Extended discussions on the need for centralized control have been presented in published works. − …”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…On the basis of the number of manipulated and controlled variables, the multivariable processes are divided into square and nonsquare systems, depending on the equality of the number of inputs and outputs. 11 Systems that present an uneven number of manipulated and controlled variables are often found in the processes of the chemical industry. The usual solution to design feedbackcontrol schemes for these systems is to eliminate or add variables to obtain a square system.…”

Section: Introductionmentioning

confidence: 99%

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Nonsquare Multivariable Chemical Processes: A Hybrid Centralized Control Proposal

Revelo

Herrera

Camacho

et al. 2020

Ind. Eng. Chem. Res.

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This paper presents a hybrid centralized control scheme for a nonsquare multivariable process. The proposed approach combines the Smith predictor, gain-scheduling methodology, and Davison method with the Particle Swarm Optimization (PSO) algorithm, all of which are combined to solve a nonsquare control-system problem that compensates for the multiple and different time delays and process nonlinearities. We call this fusion a hybrid control scheme. The Davison method does not provide a fine-tuning methodology for the centralized controller; therefore, the PSO method is added. This optimization method yields the best values for δ and ε, improving the process response with a smoother controller action, with a trade-off between the performance and robustness of the proposed controller. This method is applied to a reactor−separator−recycle (R−S−R) plant. These process types are characterized as being subjected to strong interactions among its variables and present strong nonlinearities. The R−S−R plant is modeled using the identification method based on the reaction curve, from which its equivalent transfer function (ETF) is determined. ETF represents a multivariable system with multiple time delays. In the current proposal, the nonlinearities that are present in the R−S−R system are compensated using the gain-scheduling strategy. The simulation tests verify the performance of the proposed controller, which is performed in MatLab. This controller is compared with a proportional integral (PI)-centralized controller and Smith delay compensator. All controllers are tuned using PSO.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nonsquare Multivariable Chemical Processes: A Hybrid Centralized Control Proposal

Revelo

Herrera

Camacho

et al. 2020

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

show abstract

“…Nowadays, proportional-integral (PI) and proportional-integral-derivative (PID) algorithms are the preferred control methods for most modern industrial processes because they have a simple structure and can be designed to exhibit both good performance and robustness characteristics (Flores-Estrella et al, 2016;Salazar-Pereyra et al, 2016;Estévez-Sánchez et al, 2017;Besta et al, 2018;Cruz-Rojas et al, 2019;Ma et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…However, when processes have multipleinput/multiple-output (MIMO) dynamics with complex interactions among variables, such as most chemical processes (Pathiran and Jagadeesan, 2018), the design of PI/PID controllers simultaneously achieving a correct control system operation (adequate set-point tracking, disturbance rejection and insensibility to model uncertainty) is not an easy task (Liu et al, 2010;Maghade and Patre, 2012;Ram and Chidambaram, 2015;Besta et al, 2018); moreover, the application of tuning methods developed for singleinput/single-output (SISO) plants to individual control loops may compromise performance and stability (Vu and Lee, 2010;Nandong and Zang, 2014).…”

Section: Introductionmentioning

confidence: 99%