Design and experimental realization of a robust decentralized PI controller for a coupled tank system

Mahapatro, Soumya Ranjan; Subudhi, Bidyadhar; Ghosh, Sandip

doi:10.1016/j.isatra.2018.12.003

Cited by 40 publications

(23 citation statements)

References 23 publications

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“…It was found that the systems with simplified decoupling are nominally stable, yet those with ideal and inverted decoupling are unstable, especially for non-minimum phase controlled systems [54]. If particular calculated decoupler elements are non-feasible or unstable, they can be additionally equipped with delays, extra dynamics or low-pass filters [60], [61]. Some authors proposed the design of MIMO centralized controllers implicitly or explicitly including the decoupling of control loops [58], [62]- [64].…”

Section: Introductionmentioning

confidence: 99%

“…The quadruple tank is another typical representative of the MIMO process [13], [79]- [82]. Various centralized [83], decentralized [60] control strategies or their comparisons [84] were published; however, a simplified decoupler was mostly used [60], [85]. Some researchers deservingly pointed out that non-minimum phase controlled plant operating points may occur here [81], [83], [85].…”

Section: Introductionmentioning

confidence: 99%

“…Some researchers deservingly pointed out that non-minimum phase controlled plant operating points may occur here [81], [83], [85]. However, according to the authors' best knowledge, very few results introduced disturbances for this coupled-tank process and attempted to deal with their rejection or attenuation [60].…”

Section: Introductionmentioning

confidence: 99%

“…The second and also a substantial part of this study deals with an extensive comparative numerical example on control of a linearized model of the TITO four-tank process. Besides the proposed control strategy employing the optimal pairing, a non-optimal pairing, a simplified decoupler [45], [60], the standard inverted decoupler [56], an inverted fuzzy decoupler [73], a centralized inverted PI(D) decoupling control [64], [58], and a polynomial centralized coupled approach [92], [93] are compared by simulations. The results are evaluated by various criteria including integral ones; the designing specifics and limitations are assessed as well.…”

Section: Introductionmentioning

confidence: 99%

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Control of a Multivariable System Using Optimal Control Pairs: A Quadruple-Tank Process

2020

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This paper deals with one of the possible ways to control multivariable (MIMO) control loops. The suggested control design procedure uses the so-called primary controllers, auxiliary controllers, and also correction members. Parameters of the primary controllers are determined for the optimal control pairs using arbitrary single-variable synthesis methods; namely, the modulus optimum method, the balanced tuning method, and the desired model method. The optimal control pairs are determined using the so-called relative gain array tool or the relative normalized gain array tool combined with other tools, as the condition number or the Niederlinski index. The auxiliary feedback controllers serve for ensuring a control loop decoupling. Invariance to load disturbance of a control loop is realized by using the correction members. The novelty lies especially in the combination of the original inverted decoupling with disturbance rejection and provided tuning methods. The proposed control design for a MIMO loop is verified by simulation for the two-variable controlled plant of a quadruple-tank process and evaluated by using various criteria. Moreover, a numerical comparison to some other methods is given to the reader. INDEX TERMS Control loop decoupling and invariance, multivariable control, optimal control pairs, quadruple-tank process, simulation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Control of a Multivariable System Using Optimal Control Pairs: A Quadruple-Tank Process

2020

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“…The paper of [15] proposed a method of energy-shaping for a three-tank liquid-level system. The authors of [16] presented the design and implementation method of a robust decentralized proportion integration controller based on a predefined transfer function model. In recent years, some scholars have proposed the idea of feedback linearization [17] for nonlinear systems with multi-input and multioutput (MIMO).…”

Section: Introductionmentioning

confidence: 99%

Disturbance Observer and L2-Gain-Based State Error Feedback Linearization Control for the Quadruple-Tank Liquid-Level System

Meng

et al. 2020

Energies

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This paper proposes a fresh state error feedback linearization control method with disturbance observer (DOB) and L2 gain for a quadruple-tank liquid-level system. Firstly, in terms of the highly nonlinear and strong coupling characteristics of the quadruple-tank system, a state error feedback linearization technique is employed to design the controller to achieve liquid-level position control and tracking control. Secondly, DOB is purposed to estimate uncertain exogenous disturbances and applied to compensation control. Moreover, an L2-gain disturbance attenuation technology is designed to resolve one class of disturbance problem by uncertain parameter perturbation existing in the quadruple-tank liquid-level system. Finally, compared with the classical proportion integration differentiation (PID) and sliding mode control (SMC) methods, the extensive experimental results validate that the proposed strategy has good position control, tracking control, and disturbance rejection performances.

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Robust decentralized proportional–integral controller design for an activated sludge process

Anchan

Rao

2020

Asia-Pacific J Chem Eng

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This paper presents the design of a decentralized proportional-integral (PI) controller for a wastewater treatment plant (WWTP). The aeration rate and the return recycle sludge rate are manipulated inputs to the WWTP process, while substrate and biomass concentration are considered as the output variables. The study is divided into two segments: A decentralized controller is designed based on the best pairing in the first segment, and in the second segment, a decoupler is developed to reduce the interactions. Decouplers are generally used to create independent loops in the multivariable control loops. Each decoupled subsystem is converted to first order plus time delay (FOPTD) model using a system identification toolbox to design independent diagonal controllers. The numerical simulations have been performed to evaluate the effectiveness of the presented methods. Furthermore, a robustness study has also been carried out by taking into account multiplicative input and output uncertainties, and it is found that the controller designed based on minimizing the integral of absolute error (IAE) criteria shows more robust.

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Design and experimental realization of a robust decentralized PI controller for a coupled tank system

Cited by 40 publications

References 23 publications

Control of a Multivariable System Using Optimal Control Pairs: A Quadruple-Tank Process

Control of a Multivariable System Using Optimal Control Pairs: A Quadruple-Tank Process

Disturbance Observer and L2-Gain-Based State Error Feedback Linearization Control for the Quadruple-Tank Liquid-Level System

Robust decentralized proportional–integral controller design for an activated sludge process

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