Control of the Biodegradation of Mixed Wastes in a Continuous Bioreactor by a Type-2 Fuzzy Logic Controller

2009

Abstract Type-2 fuzzy logic control is proposed for nonlinear processes characterized by bifurcations. A control simulation study was conducted for a bioreactor with cell recycle containing phenol and glucose as carbon and energy sources in which a pure culture of Pseudomonas putida is carried out. The model developed by Ajbar [Ajbar, A. (2001). Stability analysis of the biodegradation of mixed wastes in a continuous bioreactor with cell recycle. Water Research, 35 (5), 1201–1208] was used for the simulations. The particular dynamics of the bioreactor, characterized by two saddle-node bifurcations, makes its control difficult, since it may become unstable also for small variations of some p…

Type-2 fuzzy control of a fed-batch fermentation reactor

2010

Abstract The aim of the paper is to present the application of type-2 fuzzy logic controllers (T2FLCs) to the control of a fed-batch fermentation reactor in which the penicillin production is carried out. The performance of the control system using T2FLCs is compared by simulation with that of a control system using type-1 fuzzy logic controllers (T1FLCs). The non linear model used for the simulation study is an unstructured model characterized by the presence of non linearities, parameter uncertainty and measurement noise. Simulation results confirm the robustness of the T2FLC which shows a better performance than its type-1 counterpart particularly when uncertainties are present in the co…

Adaptive type-2 fuzzy logic control of a bioreactor

2010

Two adaptive type-2 fuzzy logic controllers with minimum number of rules are developed and compared by simulation for control of a bioreactor in which aerobic alcoholic fermentation for the growth of Saccharomyces cerevisiae takes place. The bioreactor model is characterized by nonlinearity and parameter uncertainty. The first adaptive fuzzy controller is a type-2 fuzzy-neuro-predictive controller (T2FNPC) that combines the capability of type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a neural network model of the nonlinear system. The second adaptive fuzzy controller is instead a self-tuning type-2 PI cont…

Control of a Non-isothermal CSTR by Type-2 Fuzzy Logic Controllers

2009

The paper describes the application of a type-2 fuzzy logic controller (FLC) to a non-isothermal continuous stirred tank reactor (CSTR) characterized by the presence of saddle node and Hopf bifurcations. Its performance is compared with a type-1 fuzzy logic controller performance. A full analysis of the uncontrolled CSTR dynamic was carried out and used for the feedback-feedforward fuzzy controllers development. Simulation results confirm the effectiveness and the robustness of the type-2 FLCs which outperform their type-1 counterparts, particularly when uncertainties are present in the system.

Nonlinear fuzzy control of a fed-batch reactor for penicillin production

2012

Abstract The process of penicillin production is characterized by nonlinearities and parameter uncertainties that make it difficult to control. In the paper the development and testing of a multivariable fuzzy control system that makes use of type-2 fuzzy sets for the control of pH and temperature are described. The performance of the type-2 fuzzy logic control system (T2FLCS) is compared by simulation with that of a type-1 fuzzy logic control system (T1FLCS) and that of a control system with traditional proportional-integral-derivative (PID) controllers proposed in the literature. The fuzzy controllers are optimized using an ANFIS algorithm. The best results are obtained with the T2FLCS pa…

Off-line control of the postprandial glycemia in type 1 diabetes patients by a fuzzy logic decision support

2012

The target of this paper is to describe the use of fuzzy techniques in the development of a decision support system that allows the optimization of postprandial glycemia in type 1 diabetes patients taking into account the kind of meal taken by patients, the preprandial glycemia and the insulin resistance (the response of the body to insulin dose injection therapy). The decision support system can, in many cases, provide patients with the correct number of rapid insulin units that must be assumed to assure an optimal glycemic profile, keeping the blood glucose level close to the homeostatic condition, several hours after the meal.

Experimental Comparison of Type-1 and Type-2 Fuzzy Logic Controllers for the Control of Level and Temperature in a Vessel

2011

Abstract The objective of this experimental study is to compare the performance of type-1 and type-2 fuzzy logic controllers on a real system where the control of liquid level and temperature are considered. By the use of genetic algorithms it is possible to optimize the fuzzy sets of each fuzzy controller assuring high control performance. The experimental results show that a better control in terms of robustness can be achieved by type-2 fuzzy logic controllers.

Control of a nonlinear continuous bioreactor with bifurcation by a type-2 fuzzy logic controller

2008

The object of this paper is the application of a type-2 fuzzy logic controller to a nonlinear system that presents bifurcations. A bifurcation can cause instability in the system or can create new working conditions which, although stable, are unacceptable. The only practical solution for an efficient control is the use of high performance controllers that take into account the uncertainties of the process. A type-2 fuzzy logic controller is tested by simulation on a nonlinear bioreactor system that is characterized by a transcritical bifurcation. Simulation results show the validity of the proposed controllers in preventing the system from reaching bifurcation and instable or undesirable s…

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

2011

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

Corrigendum to “Off-line control of the postprandial glycemia in type 1 diabetes patients by a fuzzy logic decision support” [Expert Systems with App…

2012

Development of a fuzzy expert system for the control of glycemia in type 1 diabetic patients

2011

Abstract The paper describes the structure and the characteristics of an expert system that allows the optimization of postprandial glycemia in type 1 diabetic patients. The expert system is able to provide patients with the number of rapid insulin units that must be taken in order to keep the blood glucose level close to the omeostatic condition in the hours following a meal.

Sviluppo di un sistema di supporto decisionale tipo Fuzzy per il controllo della glicemia post-prandiale nel diabete mellito tipo 1

2010

Adaptive Type-2 Fuzzy Logic Control of Non-Linear Processes

2011

The main objective of this study is to provide a valid and effective approach for the design and development of an adaptive type-2 fuzzy controller (AT2FLC), based on the analysis of the nonlinear process dynamics and the use of an ANFIS technique for the optimization of the controller. The performance of the obtained AT2FLC, characterized by a few number of rules, is higher than the performance of a traditional type-2 fuzzy controller with a larger rule base. The proposed controller is particurarly suitable for the control of processes characterized by uncertainty and time varying parameters.

Development of a predicitive type-2 neurofuzzy controller

2009

A controller that combines the main characteristics and advantages of three different control methodologies is proposed for the control of systems with nonlinearities and uncertainties. A neural network predictive control approach is implemented modifying the output of a controller with a fuzzy logic structure that uses type-2 fuzzy sets. Neural networks are also used to optimize the membership function parameters. The proposed controller is tested by simulation for the control of a bioreactor characterized by bifurcation and parameter uncertainty.

Non linear control of glycaemia in type 1 diabetic patients

2011

A fuzzy controller for the closed loop control, by insulin infusion of glycaemia in type 1 diabetic patients is proposed. The controller uses type-2 fuzzy sets. The controller was tested in simulation using a complex nonlinear model of the glucose metabolism. Simulation results confirm the effectiveness and the robustness of the type-2 fuzzy logic controller. The design of the controller uses an optimization method based on genetic algorithms. This makes the type-2 fuzzy controller more efficient and faster than a fuzzy controller with type-1 fuzzy sets, allowing a more accurate control of the glucose in the blood.

Control of a fermentator for the aerobic growth of saccharomyces cerevisiae by an adaptive type-2 fuzzy logic controller

2008

I controllori a logica fuzzy (FLCs) costituiscono una facile alternativa al controllo di sistemi che hanno un comportamento fortemente non lineare, facendo uso di fuzzy sets e di una logica fuzzy del 1° tipo. A dispetto della loro popolarità però, la ricerca ha mostrato come FLCs di 1° tipo, abbiano difficoltà a gestire e a minimizzare le incertezze presenti in un sistema. Una più grande complessità dei sistemi a logica fuzzy di 2° tipo rispetto quelli del 1° tipo, permette di gestire e conseguentemente di minimizzare gli effetti di una varietà di incertezze che non può essere direttamente gestita da FLS del 1° tipo. In questo lavoro si è considerato l’uso di un FLS del 2° tipo per il contr…