Modified approach to distillation column control

Prodanović, Saša Lj.; Nedić, Novak; Filipović, Vojislav; Dubonjić, Ljubiša M.

doi:10.2298/hemind160326028p

Cited by 3 publications

(3 citation statements)

References 23 publications

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“…There are many control strategies applied to distillation column multivariable system (Jin, Wang & Liu, 2016), (Prodanović, Nedić & Filipović & Dubonjić, 2017), in this work using decentralized decoupling structure control strategy, where the proposed method of control design involves combination of simplified decoupler, and decentralized controller (PI-like fuzzy control and modified PI fuzzy) for each loop. Figure 4 Shows controlled structure block-diagram.…”

Section: Distillation Column Controllersmentioning

confidence: 99%

Fuzzy Controller of Model Reduction Distillation Column With Minimal Rules

Alawad

ALSEADY²

2020

acs

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In this paper the control of a binary distillation column is described. This control is done with fuzzy logic, one with PI- like fuzzy controller and the other with modified PI fuzzy controller, using the minimal rules for fuzzy processing. This work is focused on model reduction of Wood and Berry binary distillation column to get the best performance. It is desired to minimize the rules in order to reduce the computation time to make a faster decision. Comparisons will be made between two versions of fuzzy controllers utilizing reduced rules to verify the outputs. The controlled variables are top composition with high concentration and bottom composition with low. To demonstrate the performance of the fuzzy PI control schemes, results are compared with a classical PI controller and optimal methods, like Differential Evolution (DE), Invasive Weed Optimization (IWO).The proposed structure is able to quickly track the parameter variation and perform better in load disturbances and also for set point changes. Then all the processes of the distillation column with it? s fuzzy controllers are simulated in MATLAB software as the results are shown.

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Section: Distillation Column Controllersmentioning

confidence: 99%

Fuzzy Controller of Model Reduction Distillation Column With Minimal Rules

Alawad

ALSEADY²

2020

acs

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“…In this paper we shall approximate the element of delay by a second-order Padé approximation. The general form of Padé approximation, according to [37][38] (24) In this paper, the approximation for n = 2 is used and, in that case, the transfer function or the process is: (25) The application of Padé approximation for delay is widely used in chemical industry [38]. This type of approximation is applied in the robust control theory [37].…”

Section: Mathematical Model Of a Cstrmentioning

confidence: 99%

“…Parameters of the PI controller are determined by selecting a point in the plane. The method was applied to the design of PI controllers for hydraulic systems with long lines [24], as well as to the design of controllers for the TITO (two inputs -two outputs) system, which describes a distillation column (Wood-Berry model) [25]. The monograph [26] is dedicated to this type of problems.…”

Section: Introductionmentioning

confidence: 99%

Design of an H∞ PI controller with given relative stability and its application to the CSTR problem

Dubonjić¹,

Filipović²,

Nedić³

et al. 2018

Hem Ind

Self Cite

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H control theory has achieved a very high level, which is not followed by appropriate applications in industry. Some reasons are: synthesis of H controllers is complex and based on the numerical Nevanlinna-Pick procedure, high order of controllers (higher than the order of the process) and sensitivity to deviation of controller coefficients (fragile controller). On the other hand, PI (PID) controllers are still dominant in industry, which places the problem of design of fixed structure controllers at the forefront. The mentioned problem is very difficult. This paper proposes a simple interactive procedure for design of H PI controllers with the presence of constraints (given the relative stability) based on Ddecomposition. The catalogue of responses to references, suppression of disturbances and minimum of H criteria of control is created. Selection of controllers, based on the catalogue, is left to the user. The application of H PI controllers to a CSTR (continuous stirred-tank reactor) is demonstrated.

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Decentralized fractional-order PIλ control applied to a TITO distillation column: a comparative study with PID and MPC

Almeida,

Lenzi,

Lenzi

2024

Cuad. Ed. Desar.

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This paper investigates the use of fractional-order PIλ (FO-PI) controllers and compares their performance with classical integer-order PID (IO-PID) and fractional-order PID (FO-PID) controllers for a two-input, two-output (TITO) distillation column. Additionally, a comparative study between FO-PI and model predictive control (MPC) is conducted on the same multivariable system. While fractional control in multivariable systems has been explored, evaluations of global performance metrics—such as integral square error (ISE), integral absolute value of error (IAE), integral time weighted absolute error (ITAE), integral time weighted square error (ITSE), and integral of manipulated variables (IU)—compared to IO-PID and MPC are still scarce. This work addresses this gap by examining these metrics alongside the steps necessary for fractional control design, including Laplace numerical inversion and controller tuning. The results demonstrate that the FO-PI controller shows superior performance compared to FO/IO-PID and MPC controllers. The global relative gain indexes show improvements, with FO-PI achieving gains of 36.9% to 59.9% compared to FO/IO-PID, and a reduction of 19% to 44.1% in global index compared to MPC. The distillation column dynamics were modeled using transfer functions, allowing for a detailed comparison of control strategies. The studies conducted in this work indicate that fractional-order controllers (FO-PI) show promise in controlling the dynamics of the TITO distillation column, as evidenced by simulations and comparison with integer-order (IO-PID) and fractional-order (FO-PID) control strategies, as well as with MPC control. The study highlights the potential benefits of using fractional controllers for a classical multivariable system, allowing to advance the state of the art of this type of control approach.

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Modified approach to distillation column control

Cited by 3 publications

References 23 publications

Fuzzy Controller of Model Reduction Distillation Column With Minimal Rules

Fuzzy Controller of Model Reduction Distillation Column With Minimal Rules

Design of an H∞ PI controller with given relative stability and its application to the CSTR problem

Decentralized fractional-order PIλ control applied to a TITO distillation column: a comparative study with PID and MPC

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