Critical review of process control strategies in anammox-mediated nitrogen removal systems

Kosgey, Kiprotich; Zungu, Phumza Vuyokazi; Kumari, Sheena; Bux, Faizal

doi:10.1016/j.jece.2022.108068

Cited by 7 publications

(2 citation statements)

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“…Let us consider system (13), where the nonlinear term f (x) is unknown, which is now considered a new unknown state variable, and the term h(x) is the uncertain nonlinear dynamic behavior of f(x), constituting an extended dynamical system as .…”

Section: Uncertainty Observer-based Estimator Designmentioning

confidence: 99%

“…In this sense, an appropriate problem formulation and its solution can derive from intensification politics. Such an operational policy can be reached via lineal proportional-integral-derivative (PID), adaptive, predictive, and linearizing, among several other controllers [9][10][11][12][13][14][15][16][17][18], with certain success. Nevertheless, a different approach lies in the framework of optimal control, where the control engineers have tuned controller parameters through cost function optimization.…”

Section: Introductionmentioning

confidence: 99%

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Bioprocess Intensification of a Continuous-Flow Enzymatic Bioreactor via Productivity Dynamic Optimization under Modeling Uncertainty

Femat,

Aguilar-López,

Mata-Machuca

2023

Fermentation

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In this contribution, a class of observer-based optimal feedback control is designed. The proposed feedback control is based on the Euler–Lagrange theoretical framework, and it is motivated by the productivity intensification from the chemical reactors, which is optimally increased. A Lagrangian is computed by employing the corresponding mass balance equation of a specifically selected biochemical compound. The resulting optimal controller is coupled with a novel uncertainty estimator with bounded feedback to derive an accurate estimation of the unknown terms and functions, mostly related to the reaction rate. Via Lyapunov analysis, it was shown that the proposed observer is asymptotically stable. The estimation of the unknown terms and functions is used by the proposed controller. The proposed methodology is applied to a generic model of an enzymatic biochemical continuous reactor with complex oscillatory dynamic behavior described by mass balance equations, so, in general, the proposed controller may be applied to any continuous stirred tank bioreactor; that is, the controller is independent of the specific kinetic functions. Numerical simulations show a satisfactory performance of the proposed control strategy.

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Section: Uncertainty Observer-based Estimator Designmentioning

confidence: 99%