Ideal, Simplified and Inverted Decoupling of Fractional Order TITO Processes

Li, Zhuo; Chen, YangQuan

doi:10.3182/20140824-6-za-1003.02107

Cited by 21 publications

(11 citation statements)

References 22 publications

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“…Even though much has been discussed for TITO processes, very few studies have been discussed for FO identification applied for TITO or multivariable processes. Recently, a decoupled method on FO-TITO processes (Li and Chen, 2014) and a multivariable FO model with time delay (San-Millan et al, 2017) have clearly shown superior performance. This study was carried out to demonstrate how non-integer models would help to understand complex processes accurately.…”

Section: Introductionmentioning

confidence: 99%

A single-step identification strategy for the coupled TITO process using fractional calculus

Kothari

Mehta

Prasad

2021

Transactions of the Institute of Measurement and Control

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The reliable performance of a complete control system depends on accurate model information being used to represent each subsystem. The identification and modelling of multivariable systems are complex and challenging due to cross-coupling. Such a system may require multiple steps and decentralized testing to obtain full system models effectively. In this paper, a direct identification strategy is proposed for the coupled two-input two-output (TITO) system with measurable input–output signals. A well-known closed-loop relay test is utilized to generate a set of inputs–outputs data from a single run. Based on the collected data, four individual fractional-order transfer functions, two for main paths and two for cross-paths, are estimated from single-run test signals. The orthogonal series-based algebraic approach is adopted, namely the Haar wavelet operational matrix, to handle the fractional derivatives of the signal in a simple manner. A single-step strategy yields faster identification with accurate estimation. The simulation and experimental studies depict the efficiency and applicability of the proposed identification technique. The demonstrated results on the twin rotor multiple-input multiple-output (MIMO) system (TRMS) clearly reveal that the presented idea works well with the highly coupled system even in the presence of measurement noise.

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Section: Introductionmentioning

confidence: 99%

A single-step identification strategy for the coupled TITO process using fractional calculus

Kothari

Mehta

Prasad

2021

Transactions of the Institute of Measurement and Control

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“…This method is very easy to implement and understand. There are different types of decoupling, such as ideal, simplified, and inverted decoupling, which are often used for industrial process control (Garrido et al, 2014;Li & Chen, 2014). Ideal decoupling is very easy to use in the design of controllers, but it is rarely employed because it has complicated decoupling elements.…”

Section: Introductionmentioning

confidence: 99%

Inverted Decoupling 2DoF Internal Model Control for Mimo Processes

Juwari¹,

Azizah²,

Handogo³

et al. 2019

IJTech

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In general, the multiple-input-multiple-output (MIMO) system is the main method of process control in industry. However, the interaction between variables in the process is a challenge when designing controllers for the system. Strong interaction worsens system performance. Inverted decoupling plays an important role in reducing interaction in the process. Internal model control (IMC) is the controller used in this research. A one degree of freedom (1DoF) IMC controller is only able to provide a good response to set-point tracking, and has a slow response to disturbance rejection. Therefore, a controller that has a good response to set-point tracking and disturbance rejection is a two degrees of freedom (2DoF) IMC. The tuning method uses maximum peak gain margin (Mp-GM) stability criteria based on the uncertainty model. In this study, a reduction in interaction was realized by the addition of inverted decoupling to the 2DoF IMC control scheme. The Wardle & Wood and Wood & Berry column distillation models are given as illustrative examples to demonstrate the performance of the inverted decoupling 2DoF IMC control scheme. A comparison is made of the IAE values of 1DoF IMC, 2DoF IMC, decoupling 2DoF IMC, and inverted decoupling 2DoF IMC, with inverted decoupling 2DoF IMC showing the lowest IAE value.

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“…Historically, fractional order control systems have been of interest to researchers for many years. This is because these controllers, when properly tuned, have been found to yield better performance compared to integer-order controllers under similar conditions (Li & Chen, 2014). Several authors have recorded tremendous progress in utilising fractional order calculus to design control systems (Monje, et al, 2008;Padula & Visioli, 2011;Zhuang, et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

On Fractional Predictive PID Controller Design Method

Edet

Katebi

2017

IFAC-PapersOnLine

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A new method of designing fractional-order predictive PID controller with similar features to model based predictive controllers (MPC) is considered. A general state space model of plant is assumed to be available and the model is augmented for prediction of future outputs. Thereafter, a structured cost function is defined which retains the design objective of fractional-order predictive PI controller. The resultant controller retains inherent benefits of model-based predictive control but with better performance. Simulations results are presented to show improved benefits of the proposed design method over dynamic matrix control (DMC) algorithm. One major contribution is that the new controller structure, which is a fractional-order predictive PI controller, retains combined benefits of conventional predictive control algorithm and robust features of fractional-order PID controller.

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Ideal, Simplified and Inverted Decoupling of Fractional Order TITO Processes

Cited by 21 publications

References 22 publications

A single-step identification strategy for the coupled TITO process using fractional calculus

A single-step identification strategy for the coupled TITO process using fractional calculus

Inverted Decoupling 2DoF Internal Model Control for Mimo Processes

On Fractional Predictive PID Controller Design Method

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