A new control method for MIMO first order time delay non-square systems

Chen, Juan; He, ZeFang; Qi, Xin

doi:10.1016/j.jprocont.2011.01.007

Cited by 80 publications

(57 citation statements)

References 5 publications

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“…During the controller design of internal model system with multivariable time delay, the encountered mathematical model is often composed by two or more delay parts combined with the non-minimum phase model [1], [2] …”

Section: Approximate Model Structurementioning

confidence: 99%

“…During the design and implementation of the multivariate multiple time delay system, mathematical model of control plant is relatively complex after decoupling [1], [2], so, model approximation is often needed to simplify the design of the controller. Model approximation causes a wide attention in the field of industrial control especially in the process of model predictive control and model optimization [3].…”

Section: Introductionmentioning

confidence: 99%

“…Although paper [12] proposed a frequency weighted recursive least squares (FRLS) algorithm solved one case of the complex model and made some achievements, but the derivation formula of the frequency-domain weighted recursive least squares algorithm is complex, besides it needs to introduce a new external loop to solve time delay parameters, the calculation of which is tedious and inconvenience in engineering application, what's more, the paper [12] did not study of the non-minimum phase system. Other papers, genetic algorithm is used for model approximation [1], but it needs large amount of calculation and optimization process may easily fall in premature, when encounters a complex problem, the computation time will be a problem that largely affecting the industrial implementation. However, the Suboptimal reduction algorithm in paper [10], [11] has the advantages of simple calculation, good delay fitting features, and can keep the stability of the original system.…”

Section: Introductionmentioning

confidence: 99%

“…However, the Suboptimal reduction algorithm in paper [10], [11] has the advantages of simple calculation, good delay fitting features, and can keep the stability of the original system. Hence, aiming at this problem, the suboptimal reduction algorithm is been extended to approximate the multivariable multiple time delay systems and multivariable multiple time delay systems combined with non-minimum phase system [1], [2] in this paper.…”

Section: Introductionmentioning

confidence: 99%

“…And choose a reasonable error evaluation index is the basis to evaluate whether approximate model is good or bad. Based on multivariable multiple time delay systems or multivariable multiple time delay systems combined with non-minimum phase system which is often encountered in internal model control [1], [2] This paper proposes an approximate model structure and a Suboptimal approximate method, as well as the error metrics quality for evaluating the model approximation performance, The approximate results are compared with frequency-domain weighted RLS method. This paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

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Model Approximate Method of Complex System

Chen¹

2015

IJMO

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Abstract-During the internal model control of multivariate multiple time delay system, process model is very important in the design of controller, but complicated mathematical model is often encountered in decoupled multivariable multiple time delay system and needs to be reduced order. So this paper proposes a low order identification structure and an optimization method for model approximation of the complex model containing the time delay and non-minimum phase parts. In this paper, with the adoption of Pade approximation, a suboptimal approximate algorithm is used for the model approximation and model identification. The integral square error index and the frequency-domain integral square error index, as well as the integral time absolute error index is used to evaluate the approximate model comprehensively. Simulation results show that using the proposed model identification structure and adopting the suboptimal approximate algorithm to deal with this kind of approximation, that can get an approximate model that well reveals the dynamic characteristics of system and has a high approximation precision.Index Terms-Model approximation, complicated model, suboptimal approximate algorithm, error performance index.

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Section: Approximate Model Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Model Approximate Method of Complex System

Chen¹

2015

IJMO

Self Cite

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Comparative Analysis of Different Control Strategies for a Train of Cryogenic ¹³C Separation Columns

2015

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Carbon isotopes are widely used in numerous industries, especially in medicine. The advantage of using 13C‐labeled products is only shadowed by the difficulty of increasing the natural concentration. One method available is a train of cryogenic distillation columns. This paper presents a preliminary analysis of three different control strategies for a unit comprising three 7‐m‐high isotope separation columns: a decentralized multivariable proportional‐integral controller and two decoupling control algorithms. For the first one, a single controller is designed for the entire distillation column train, whereas for the second decoupling approach, three separate controllers are designed for each of the three columns. Simulation results show that the last approach provides significantly improved results when compared to the other two control strategies.

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An internal model controller design procedure for multivariable system based on the double‐decomposition

Jin

Liu

2014

Can J Chem Eng

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A novel design procedure of internal model controller based on the Double-Decomposition (DD), which includes the Full Rank Decomposition (FRD) and Singular Value Decomposition (SVD), is proposed for the multivariable system with multiple time-delay plant. In the controller design process, the Reflexive Generalised Inverse Matrix (RGIM) based on FRD is used to replace the generalised inverse matrix to design the internal model controller; improved filter based on SVD is introduced into the design process. In the FRD process for a non-square system, the Effective Relative Gain Array (ERGA) is applied to select the linear independent column. After model reduction for the internal model controller, the expression of the controller is obtained. Then the square system and the non-square system are taken as examples. The simulation results show the effectiveness of the proposed approach for the multivariable system with the multiple time-delay plant.

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A new control method for MIMO first order time delay non-square systems

Cited by 80 publications

References 5 publications

Model Approximate Method of Complex System

Model Approximate Method of Complex System

Comparative Analysis of Different Control Strategies for a Train of Cryogenic ¹³C Separation Columns

An internal model controller design procedure for multivariable system based on the double‐decomposition

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A new control method for MIMO first order time delay non-square systems

Cited by 80 publications

References 5 publications

Model Approximate Method of Complex System

Model Approximate Method of Complex System

Comparative Analysis of Different Control Strategies for a Train of Cryogenic 13C Separation Columns

An internal model controller design procedure for multivariable system based on the double‐decomposition

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Product

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Comparative Analysis of Different Control Strategies for a Train of Cryogenic ¹³C Separation Columns