Adaptive Fuzzy Control of a Process with Bifurcations

Lampo, C. Montana; Bartolozzi, V.; Picciotto, A.; Galluzzo, M.

doi:10.1007/978-88-470-2208-9_14

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…Its model and parameter values have been proposed by Ajbar [7]. The set of ordinary differential equations that constitutes the bioreactor mathematical model is reported in (1) together with the reaction rate expressions.…”

Section: A Continuous Bioreacormentioning

confidence: 99%

“…More recently type-2 fuzzy logic controllers have been applied in vehicle nonlinear active suspension systems [3], in autonomous mobile robot control [4] and in biochemical reactor control [5], [6]. In this paper a continuous bioreactor with cell recycle [7] is considered. In the bioreactor the biodegradation of mixed wasted is carried out and the process shows a behavior characterized by bifurcations for particular values of some parameters.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive type-2 fuzzy control of non-linear systems

Galluzzo

Cosenza

2009

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems

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The paper describes the development of two different type-2 adaptive fuzzy logic controllers and their use for the control of a non linear system that is characterized by the presence of bifurcations and parameter uncertainty. Although a type-2 fuzzy logic controller is able to handle the non linearities and the uncertainties present in a system, its robustness and effectiveness can be increased by the use of an opportune adaptive algorithm. A simulation study was conducted to compare the behavior of adaptive controllers with that of simple type-1 and type-2 fuzzy logic controllers. The system to be controlled, used for the simulation, is a continuous bioreactor for the treatment of mixed wastes in which a culture of Pseudomonas Putida is carried out while phenol and glucose are carbon and energy sources. From simulations results it can be seen that both adaptive controllers, but in particular the self tuning controller, have a better performance being able to eliminate oscillations that are present with basic fuzzy controllers.

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Section: A Continuous Bioreacormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive type-2 fuzzy control of non-linear systems

Galluzzo

Cosenza

2009

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems

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“…The reactor temperature x 3 oscillates with increasing amplitude until it reaches a constant oscillation amplitude: the reactor moves from the stable region to the unstable region (from A to B in the continuity diagram of Fig. 1) [37].…”

Section: Analysis Of the Reactor Dynamicsmentioning

confidence: 99%

Control of a non-isothermal continuous stirred tank reactor by a feedback–feedforward structure using type-2 fuzzy logic controllers

Galluzzo

Cosenza

2011

Information Sciences

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A control system that uses type-2 fuzzy logic controllers (FLC) is proposed for the control of a\ud non-isothermal continuous stirred tank reactor (CSTR), where a first order irreversible\ud reaction occurs and that is characterized by the presence of bifurcations. Bifurcations due\ud to parameter variations can bring the reactor to instability or create new working conditions\ud which although stable are unacceptable. An extensive analysis of the uncontrolled CSTR\ud dynamics was carried out and used for the choice of the control configuration and the development\ud of controllers. In addition to a feedback controller, the introduction of a feedforward\ud control loop was required to maintain effective control in the presence of disturbances.\ud Simulation results confirmed the effectiveness and the robustness of the type-2 FLC which\ud outperforms its type-1 counterpart particularly when system uncertainties are present

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Adaptive Fuzzy Control of a Process with Bifurcations

Cited by 2 publications

References 11 publications

Adaptive type-2 fuzzy control of non-linear systems

Adaptive type-2 fuzzy control of non-linear systems

Control of a non-isothermal continuous stirred tank reactor by a feedback–feedforward structure using type-2 fuzzy logic controllers

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