An adaptive super-twisting sliding mode algorithm for robust control of a biotechnological process

In this paper, a robust super-twisting sliding mode control with adaptive tuning law is developed for a nonlinear biotechnological process, which takes place inside a continuous stirred tank bioreactor. A super-twisting algorithm (STA) is firstly designed to obtain high robustness as well as preserv...

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Bibliographic Details
Published in:International journal of dynamics and control 2020-06, Vol.8 (2), p.581-591
Main Authors: Bouyahia, Semcheddine, Semcheddine, Samia, Talbi, Billel, Boutalbi, Oussama, Terchi, Younes
Format: Article
Language:English
Subjects:
Adaptive algorithms
Adaptive control
Algorithms
Bioreactors
Complexity
Computer simulation
Continuously stirred tank reactors
Control
Control and Systems Theory
Control theory
Dynamical Systems
Engineering
Robust control
Sliding mode control
Stability criteria
Tuning
Twisting
Uncertainty
Vibration
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Summary:In this paper, a robust super-twisting sliding mode control with adaptive tuning law is developed for a nonlinear biotechnological process, which takes place inside a continuous stirred tank bioreactor. A super-twisting algorithm (STA) is firstly designed to obtain high robustness as well as preserve fast convergence with high accuracy. The benefit of this approach is that its design procedure is independent of the prior knowledge of the bound value of the uncertainties and perturbations. However, the STA has a drawback that provides a chattering in the control loop. In order to overcome this drawback, an adaptive tuning algorithm is developed to adjust the STA control law without frequency switching and alleviate the undesired chattering phenomenon. Then, the robustness can be achieved despite the existence of the unknown uncertainties and external perturbations for the nonlinear process. In addition, a formal proof of the global uniform asymptotic stability based on Lyapunov criterion of the closed-loop process is derived. Several simulation results show that the proposed adaptive super-twisting algorithm guarantees the performance of the STA under external disturbance and parametric uncertainty with less chattering and illustrate the overall performance improvements.
ISSN:2195-268X
2195-2698
DOI:10.1007/s40435-019-00551-8