Design of Smith Predictor and Fuzzy Decoupling for Mimo Chemical Processes with Time Delays

Hamdy, Mohamed; Ramadan, Abdalhady

doi:10.1002/asjc.1338

Cited by 17 publications

(7 citation statements)

References 20 publications

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“…The results, when compared with the experimental values, demonstrated the robustness of the tool. To overcome the problem of time delay in the MIMO chemical process, Hamdy and Ramadan [28] used Simulink to design a Smith's predictor based on a decoupling scheme, to reduce the interaction that occurs between its strategic variables. A binary distillation column and an industrial-scale polymerization reactor model were used as two examples to illustrate the feasibility of the proposal and the success of the simulation tool.…”

Section: Introductionmentioning

confidence: 99%

Distributed Control Strategy with Smith's Predictor in a Pilot‐Scale Diabatic Distillation Unit

et al. 2020

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Intrinsic characteristics of distillation such as dead time and high nonlinearities do not allow the complete elimination of transient times when any external disturbance or set‐point change occurs. Thus, aiming at the use of easy‐tuning systems, a distributed‐action control in trays of a diabatic distillation unit with Smith's predictor was implemented in the Simulink environment to further reduce transient times and out‐of‐specification product. The distributed‐action strategy with Smith's predictor led to a reduction of 33.3 min (33 %) in the transient time of the top temperature control loop and 66 % in out‐of‐specification product, when compared with the conventional strategy, and thus is shown to be an efficient approach to increasing the productivity of distillation plants.

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Section: Introductionmentioning

confidence: 99%

Distributed Control Strategy with Smith's Predictor in a Pilot‐Scale Diabatic Distillation Unit

et al. 2020

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“…Controlling this type of MIMO system using multidimensional fuzzy control strategies is difficult; therefore, a multilevel control method is adopted. Fusion function theory can be used to convert the complex fuzzy control strategy into a more simplified nested control strategy [18,19], as follows:…”

Section: Fusion Function Designmentioning

confidence: 99%

“…In this paper, the d 1 k values of the 5-meter deployable antenna are unknown. Equation (19) represents an SISO system with disturbances and a one-to-one relationship between the input and output of the 1st decoupled subsystem exists.…”

Section: Ardfd Controller Designmentioning

confidence: 99%

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Adaptive Reduced Dimension Fuzzy Decoupling Control Method with Its Application to a Deployable Antenna Panel

Liu

Bao

et al. 2018

International Journal of Aerospace Engineering

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This paper addresses the multiple-input multiple-output (MIMO) control problem with an active deformation adjustment mechanism on a 5-metre deployable antenna panel. An adaptive reduced-dimension fuzzy decoupling (ARDFD) control strategy based on fusion functions is proposed to eliminate the effects uncertainties due to coupled subsystems by designing and incorporating a fuzzy decoupling disturbance observer. Moreover, the MIMO system can be decomposed into a number of single-input single-output (SISO) systems using the unit diagonal matrix decoupling theory. Based on Lyapunov stability theory, it was shown that the error of fuzzy interference observer and the error between the fuzzy rule post parameter matrix and optimal post parameter matrix converge to a small region. Results of the simulation also show that the ARDFD control strategy can significantly eliminate adverse effects of the coupled subsystems.

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“…Most often, it boils down to minimization of the coupling effects instead of full decoupling. As control of MIMO dynamic systems enjoys a continuous attention [1], [2], a challenging task becomes to include the dynamic decoupling problem [3]- [14].…”

Section: Introductionmentioning

confidence: 99%

Effective Use of MPC for Dynamic Decoupling of MIMO Systems

Dworak¹,

Goyal²,

Aggarwal³

et al. 2019

ElAEE

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The article analyses possible ways of using predictive controllers to perform control tasks and dynamic decoupling for dynamic systems with Multiple Inputs and Multiple Outputs (MIMO). The results of experiments on the selected reference plant are presented, showing the effectiveness of individual decoupling methods. These are also compared to those obtained in typical control systems with Proportional-Integral-Derivative (PID) controllers. Recommendations are made on how to tune model predictive controllers (MPC) for their effective use for MIMO plants.

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Design of Smith Predictor and Fuzzy Decoupling for Mimo Chemical Processes with Time Delays

Cited by 17 publications

References 20 publications

Distributed Control Strategy with Smith's Predictor in a Pilot‐Scale Diabatic Distillation Unit

Distributed Control Strategy with Smith's Predictor in a Pilot‐Scale Diabatic Distillation Unit

Adaptive Reduced Dimension Fuzzy Decoupling Control Method with Its Application to a Deployable Antenna Panel

Effective Use of MPC for Dynamic Decoupling of MIMO Systems

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