Centralized multivariable control by simplified decoupling

Garrido, Juan; Vázquez, Francisco; Morilla, Fernando

doi:10.1016/j.jprocont.2012.04.008

Cited by 73 publications

(64 citation statements)

References 27 publications

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“…Using configuration 1-2 (depicted in Figure 3), the following expressions (9) for the non-zero controller elements are obtained from (5) and (6 In the configuration 2-1 (Figure 4), the general expressions for the controller elements are given by (10), which are obtained from (5) and (6). The corresponding general expressions for conventional centralized decoupling control for 2×2 processes that are obtained according to (1) are given by (11).…”

Section: Centralized Inverted Decoupling Control For 2×2 Processesmentioning

confidence: 99%

“…In the first case, a decoupler [8][9][10][11][12][13][14][15][16] is used to minimize interaction or to make the system diagonal dominant; then, the controllers are designed using some decentralized method. Figure 1a shows the general control scheme of this approach where G(s), D(s) and C(s) are the process matrix, the decoupling matrix and the decentralized control matrix, respectively.…”

Section: Introductionmentioning

confidence: 99%

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Centralized Inverted Decoupling Control

Garrido

Vázquez

Morilla

2013

Ind. Eng. Chem. Res.

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Abstract:This paper presents a new methodology of multivariable centralized control based on the structure of inverted decoupling. The method is presented for general n×n processes, obtaining very simple general expressions for the controller elements with a complexity independent of the system size. The possible configurations and realizability conditions are stated. Then, the specification of performance requirements is carried out from simple open loop transfer functions for three common cases. As a particular case, it is shown that the resulting controller elements have PI structure or filtered derivative action plus a time delay when the process elements are given by first order plus time delay systems. Comparisons with other works demonstrate the effectiveness of this methodology through the use of several simulation examples and an experimental lab process.

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Section: Centralized Inverted Decoupling Control For 2×2 Processesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Centralized Inverted Decoupling Control

Garrido

Vázquez

Morilla

2013

Ind. Eng. Chem. Res.

Self Cite

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“…The gradient descent method can be used to adjust the velocity. For function f (X), X = (x 1 , x 2 , · · · , x n ), the gradient is shown in Equation (9).…”

Section: Adaptive Parameters Adjustmentmentioning

confidence: 99%

“…PID control technique has been widely used in the real control system for its advantages such as simple mechanism and clear physical conception. It is hard to get a precise control performance even while researchers focus on other intelligent control methods, including adaptive control [1,2], fuzzy control [3,4,5], neural network control [6,7,8] and decoupling control [9,10,11] etc.. And then, some mixed control methods are emerging, such as PID neural network. Due to the characteristics of self-learning, self-organizing and self-adaptation, PID neural network would automatically identify the controlled system parameters and automatically adjust the parameters according to the changes in the process parameters.…”

Section: Introductionmentioning

confidence: 99%

An adaptive PID neural network for complex nonlinear system control

et al. 2014

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Usually it is difficult to solve the control problem of a complex nonlinear system. In this paper, we present an effective control method based on adaptive PID neural network and particle swarm optimization (PSO) algorithm. PSO algorithm is introduced to initialize the neural network for improving the convergent speed and avoiding weights getting trapped into local optima. To adapt the initially uncertain and varying parameters in the control system, we introduce an improved gradient descent method to adjust the network parameters. The stability of our controller is analyzed according to the Lyapunov method. The simulation of complex nonlinear multiple-input and multiple-output (MIMO) system is presented with strong coupling. Empirical results illustrate that the proposed controller can obtain good precision with shorter time compared with the other considered methods. It provides a novel control approach for complex nonlinear systems.

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“…For example, Garrido et al [20] proposed a centralized control design, which was based on the simplified decoupling technique. Here, it was shown that the decoupler elements that are set to unity might not be necessarily the diagonal elements.…”

Section: Introductionmentioning

confidence: 99%

Inter-Communicative Decentralized Multi-Scale Control (ICD-MSC) Scheme: A New Approach to Overcome MIMO Process Interactions

Nandong

Zang

2014

Chemical Product and Process Modeling

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Decentralized PID control has been extensively used in process industry due to its functional simplicity. But designing an effective decentralized PID control system is very challenging because of process interactions and dead times, which often impose limitations on control performance. In practice, to alleviate the detrimental effect of process interactions on control performance, decoupling controllers are often incorporated into a decentralized control scheme. In many cases, these conventional decoupling controllers are not physically realizable or too complex for practical implementation. In this paper, we propose an alternative scheme to overcome the performance limitation imposed by process interactions. This new control scheme is extended from the SISO multi-scale control scheme previously developed for nonminimum-phase processes. The salient feature of the new control scheme lies in its communicative structure enabling collaborative communication among all the sub-controllers in the system. This communicative structure serves the purpose of reducing the detrimental effect of process interactions leading to improved control performance and performance robustness. Extensive numerical study shows that the new control scheme is able to outperform some existing decentralized control schemes augmented with traditional decoupling controllers.

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Centralized multivariable control by simplified decoupling

Cited by 73 publications

References 27 publications

Centralized Inverted Decoupling Control

Centralized Inverted Decoupling Control

An adaptive PID neural network for complex nonlinear system control

Inter-Communicative Decentralized Multi-Scale Control (ICD-MSC) Scheme: A New Approach to Overcome MIMO Process Interactions

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