Real-time implementation of multi-linear model-based control strategies––an application to a bench-scale pH neutralization reactor

Galán, Omar; Romagnoli, José A.; Palazoğlu, Ahmet

doi:10.1016/j.jprocont.2003.10.003

Cited by 79 publications

(51 citation statements)

References 11 publications

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“…The process consists of the neutralization reaction between a strong acid (HA) and a strong base (BOH) in the presence of a buffer agent (BX) as described by Galán et al (2004). The neutralization takes place in a continuous stirred tank reactor (CSTR) with a constant volume V. In this reactor, an inlet acidic solution of composition x 1i (t) and a time-varying volumetric flow q A (t) is neutralized using an alkaline solution of volumetric flow q B (t) and known composition made up of base x 2i and buffer agent x 3i .…”

Section: Process Descriptionmentioning

confidence: 99%

ROBUST CONTROL OF WIENER SYSTEMS: APPLICATION TO A pH NEUTRALIZATION PROCESS

Biagiola

Agamennoni

Figueroa

2016

Braz. J. Chem. Eng.

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-In this paper, the robustness of a typical control scheme for Wiener systems is studied. These systems consist of the cascade connection of a linear time invariant system and a static nonlinearity. To control this kind of systems, several approaches were discussed in the literature. Most of these control schemes involve transformation of the measured variable as well as the setpoint, by the inverse of the nonlinear gain. The approach followed in this work uses the inverse model of the static nonlinear gain, while the uncertainty in the Wiener model is treated as a partitioned problem. The linear block is considered as a parameter-affine-dependent model and, on the other hand, the nonlinear block uncertainty is analyzed as a conic-sector. The robustness analysis is performed using -theory. The results are evaluated on the basis of a simulation of a pH neutralization process.

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Section: Process Descriptionmentioning

confidence: 99%

ROBUST CONTROL OF WIENER SYSTEMS: APPLICATION TO A pH NEUTRALIZATION PROCESS

Biagiola

Agamennoni

Figueroa

2016

Braz. J. Chem. Eng.

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“…Very good and representative overview of the older references dealing with this subject can be found in work of Wright and Kravaris [30]. However, since then, the progress in pH control is still being made and among many others, let us mention the application of the Wiener model with the feedforward action [17], of the adaptive backstepping state feedback controller [32] and of other multi-model adaptive control strategies [6,13]. There are also extensive studies on the application of the fuzzy logic systems and neural networks to control pH processes, e.g.…”

Section: Introductionmentioning

confidence: 99%

Improving efficiency of pH control by balance-based adaptive control application

Stebel¹,

Czeczot²,

Metzger³

2013

Archives of Control Sciences

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This paper deals with the efficient control of the pH process. Considering the PI + gain scheduling (PI+GS) controller as the benchmark and its control performance as the base, we investigate experimentally the overall improvement in the control performance obtained by the application of the Balance-Based Adaptive Controller (B-BAC), which requires only the measurement data of the flow rates and pH values. The improvement of the control efficiency is investigated not only in terms of the controlled variable performance but also in terms of the manipulated variable performance considered as the considerable control cost. The application of the B-BAController can ensure lower controlled pH variability at the price of the control effort similar to the PI+GS approach and thus it can improve the overall efficiency of pH control. The second important contribution is the experimental validation of the very simple and intuitive tuning procedure for the B-BAController.

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“…Yoon, Yang, and Kang (2002) presented an adaptive backstepping state feedback controller, and shown stability of the proposed scheme. Multi-model adaptive control schemes have been also developed and evaluated for nonlinear pH neutralization processes (Boling, Seborg, & Hespanha, 2007;Dougherty & Cooper, 2003;Galan, Romagnoli, & Palazoglu, 2004;Pishvaie & Shahrokhi, 2000). Several other adaptive nonlinear pH controllers have been proposed in the relevant literature (Gustafsson & Waller, 1983;Jutilia, 1983;Li & Biegler, 1990;Pajunen, 1985;Panish & Brosilow, 1988;Williams, Rhinehart, & Riggs, 1990).…”

Section: Introductionmentioning

confidence: 99%