2009
DOI: 10.1177/0142331208100893
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Sliding mode controlled bioreactor using a time-varying sliding surface

Abstract: Bioreactor processes based on substrate concentration have both highly non-linear behaviour and parameter uncertainties mostly bounded with physical and biological constraints, which make them a subject area of sliding mode control. This work deals with sliding mode control of a fermentation process in a continuous stirred bioreactor. A new sliding surface is defined using angular information as a function of time that provides adjustable continuous movement of the sliding surface. Computer simulations are pre… Show more

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Cited by 25 publications
(18 citation statements)
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References 28 publications
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“…This modified exponential function in its basic form allows for the controller to have strong actuation for small errors. This is related to the sigmoidal functions proposed in [11], [13], and [14], but the exponential mapping is more flexible in the sense that it can also generate a weak actuation for higher errors.…”
Section: Emc Implementationmentioning
confidence: 98%
See 1 more Smart Citation
“…This modified exponential function in its basic form allows for the controller to have strong actuation for small errors. This is related to the sigmoidal functions proposed in [11], [13], and [14], but the exponential mapping is more flexible in the sense that it can also generate a weak actuation for higher errors.…”
Section: Emc Implementationmentioning
confidence: 98%
“…Another idea [13] was the use of a parabolic function coupled to a shifted sigmoid function to change the linear discontinuous control with the equivalent term computed with a simplified, model-based piecewise function. This nonlinear parabolic sliding surface was:…”
Section: Dynamic Smc Tuningmentioning
confidence: 99%
“…In the particular case of fed-batch bioreactors, some nonlinear control strategies were developed to improve the process efficiency and the "batch-to-batch" reproducibility [6], as well as to deal with the unavoidable uncertainties typically present in bioprocesses [7].…”
Section: Introductionmentioning
confidence: 99%
“…Using the exact linearization and estimation algorithms in [34], a nonlinear adaptive controller was proposed for a fed-batch bioprocess. In [38], the adaptive control for bioreactors is improved through sliding mode control. The gain-scheduling methods and adaptive control are combined in [15] to control the pH of a bioreactor in a fermentation processes.…”
Section: Introductionmentioning
confidence: 99%