Multiple Model Predictive Control of Multivariable pH Process Using Adaptive Weighting Matrices

Bagheri, Peyman; Mardanlou, Vahid; Fatehi, Alireza

doi:10.3182/20110828-6-it-1002.02940

Cited by 8 publications

(1 citation statement)

References 13 publications

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“…This transfer function matrix has been obtained by linearization of the system around the operating point y 1 = PH = 7.7, y 2 = 16 cm. 48 The following state-space representation is used in our control design for the pH system (24):…”

Section: Fault-tol Erant Fixed-order Control For a Ph Control Systemmentioning

confidence: 99%

Multiobjective fault‐tolerant fixed‐order/PID control of multivariable discrete‐time linear systems with unmeasured disturbances

Karimi

Batmani

Khosrowjerdi

2018

Optim Control Appl Methods

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In this paper, a multiobjective fault-tolerant fixed-order output feedback controller design technique is proposed for multivariable discrete-time linear systems with unmeasured disturbances. Initially, a multiobjective fixed-order controller is designed for the system by transforming the problem of tuning the parameters of the controller into a static output feedback problem and solving a mixed H 2 ∕H ∞ optimization problem with bilinear matrix inequalities.Subsequently, the fixed-order controller is used to construct the closed-loop system and an active fault-tolerant control scheme is applied using the input/output data collected from the controlled system. Motivated by its popularity in industry, the proposed method is also used to tune the parameters of proportional-integral-derivative controllers as a special case of structured controllers with the fixed order. Two numerical simulations are provided to demonstrate the design procedure and the flexibility of the proposed technique.

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Section: Fault-tol Erant Fixed-order Control For a Ph Control Systemmentioning

confidence: 99%

Multiobjective fault‐tolerant fixed‐order/PID control of multivariable discrete‐time linear systems with unmeasured disturbances

Karimi

Batmani

Khosrowjerdi

2018

Optim Control Appl Methods

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Coagulation process control in water treatment plants using multiple model predictive control

Bello

Hamam

Djouani

2014

Alexandria Engineering Journal

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Model predictive control of pH neutralization processes: A review

Hermansson

Syafiie

2015

Control Engineering Practice

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The paper provides a review of the different approaches of Model Predictive Control (MPC) to deal with the nonlinearities and transient behavior associated with pH and its control. Firstly a description of the pH system and what makes it difficult to control is presented, followed by the general description of the structure of MPC. The different applications of MPC vary mostly in the way the model is described and how the optimization is carried out to obtain the desired control action. The different modeling techniques applied to the MPC, which is used to describe the behavior of the pH are ranging from simple linear models, multiple linear models like piecewise linear descriptions and fuzzy models, to nonlinear descriptions like Wiener models and the use of artificial neural networks. The models and their respective ways of application are reviewed. Finally, the areas where more research is needed are addressed.

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Multiple Model Predictive Control of Multivariable pH Process Using Adaptive Weighting Matrices

Cited by 8 publications

References 13 publications

Multiobjective fault‐tolerant fixed‐order/PID control of multivariable discrete‐time linear systems with unmeasured disturbances

Multiobjective fault‐tolerant fixed‐order/PID control of multivariable discrete‐time linear systems with unmeasured disturbances

Coagulation process control in water treatment plants using multiple model predictive control

Model predictive control of pH neutralization processes: A review

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