Control configuration selection for multi input multi output processes

Sujatha, V.; Panda, Rames C.

doi:10.1016/j.jprocont.2013.09.012

Cited by 15 publications

(11 citation statements)

References 8 publications

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“…The control algorithms were applied in gPROMS against various tuning parameters and concluded that optimizing controller can be easily applied to a simulated complex model of reactive distillation to enable real time dynamic optimization. Sujatha et al [48] have considered a MIMO system defining integration of manipulated variable and control variable. Various novel techniques such as relative gain array, Niederlinski index, singular value decomposition, Morari Resiliency Index, dynamic relative gain array, hankel interaction index array, participation matrix and H 2 -norm were studied for the interactions and subsequently for input output pairing.…”

Section: Control Of Reactive Distillation Using Soft Sensors/soft Conmentioning

confidence: 99%

A Review on AI Control of Reactive Distillation for Various Applications

Sakhre¹

2021

Promising Techniques for Wastewater Treatment and Water Quality Assessment

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In this chapter, previous studies on reactive distillation process control including control using conventional as well as soft sensor control, membrane assisted reactive distillation design and simulation, estimation and control are discussed. The review of literature in different dimensions is carried out to explore the opportunities in the field of research work. The chapter is focused on dynamics and control of Reactive distillation, its control using Conventional Techniques, Model Predictive Control MPC), Reactive Distillation using Soft Sensors/Soft Controllers, Membrane assisted reactive distillation, Biodiesel in Reactive Divided Wall Column: Design and Control and Membrane reactive divided wall column. These control techniques are proposed and analyzed by many researchers. These techniques have potential use in process industries to have better soft sensor control of nonlinear processes.

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Section: Control Of Reactive Distillation Using Soft Sensors/soft Conmentioning

confidence: 99%

A Review on AI Control of Reactive Distillation for Various Applications

Sakhre¹

2021

Promising Techniques for Wastewater Treatment and Water Quality Assessment

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“…The square system that have two inputs (m 1 and m 2 ) and three outputs (y 1 and y 3 ) are considered. The proposed method of loop pairing is done by comparing the area under undesired responses for both diagonal and off-diagonal pairing, as given by Sujatha et al (2013b). The pair that offers minimum area is chosen as a judicious loop pairing.…”

Section: Control Configuration Selection Of Non-square Systemsmentioning

confidence: 99%

“…Further for two input two output system modelling and parameter estimation was proposed by Sujatha and Panda (2012). Sujatha and Panda (2013b) derived the novel method of interaction measure to select the proper input-output pairs. Mnasser and Bouani (2015) proposed the robust predictive controller for a class of multi-input–multi-output non-linear systems.…”

Section: Introductionmentioning

confidence: 99%

Time domain modeling and control of complex non-linear chemical processes using relay feedback test

Sujatha

Panda

2020

Transactions of the Institute of Measurement and Control

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This study analyzes with the technology of auto tuning using relay feedback test for non-square MIMO system through process modeling, identification, input-output pairing and control strategies. However, the control configuration selection based on conventional steady-state Relative Gain Array (RGA) matrix sometimes degrades the loop performance and it needs attention. This study also deals with the real challenges in time domain modeling and appropriate pairing of loops for non-linear chemical processes. The choice of input-output pairing for square system has been extended to non-linear chemical processes. This ensures the system’s stability by selecting an appropriate manipulated-controlled variable pairing in non-linear chemical processes and the same is also tested for benchmark of non-linear chemical processes. In this study, two types of non-square systems are considered: one is systems with excess input than output variables and the other is systems with excess output than input variables. Some benchmark non-linear chemical processes, such as processes with mild nonlinearity, moderate to high nonlinearity and highly nonlinearity, are also taken for this study. Three standard benchmark processes are used in analysis of nonlinear chemical processes, namely: (1) Continuous Stirred Tank Reactor (CSTR) process; (2) hydrogen-ion- concentration (pH) process and (3) distillation column and this procedure is illustrated via simulation of 3-by-2 and 2-by-3 non-linear chemical processes.

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“…Several solutions are presented in literature to overcome this problem. Choosing the best configuration that presents the small level of interaction is one of possible ways that designers and engineers take into consideration, however this method presents some limitations according to the tools used to assess the interactions and the difficulties faced in the implementation of some control schemes, since there are some configurations that can be deduced theoretically and might give good results but it cannot be implemented due to some other practical limitations (Kurt and Kurt 1990;Xiong et al 2005;Deeptanshu et al 2011;Khelassi et al 2012;Sujatha and Panda 2013;Potts et al 2015). Another possible way is the use of de-couplers, this method and similar to the first presents very good results in the theoretical part but in the realisation part still face many difficulties (Garrido et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Contribution to improve the dynamic control of a binary distillation column

Schulte

Bentarzi

2016

Int J Syst Assur Eng Manag

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Conventionally, steady state design for distillation column is often completed before dynamics and control issues are considered. The aim of this paper is to use the design issues as a tool to improve dynamic behavior of binary distillation column. The idea is augmenting the liquid holdup in the feed plate through a middle vessel. The degree of interactions between the loops are examined for five well known control schemes by considering different quantities of liquid holdup in the feed plate. Simulation results show that augmenting the hold-up in the feed plate will lead to minimize the interactions between the loops in all cases particularly for DV control scheme where a total decoupling is achieved.

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Control configuration selection for multi input multi output processes

Cited by 15 publications

References 8 publications

A Review on AI Control of Reactive Distillation for Various Applications

A Review on AI Control of Reactive Distillation for Various Applications

Time domain modeling and control of complex non-linear chemical processes using relay feedback test

Contribution to improve the dynamic control of a binary distillation column

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