Search results for "Fuzzy logic"
showing 10 items of 470 documents
Future is where concepts, theories and applications meet (also in fuzzy logic)
2015
No one knows where the future lies, and the idea of serendipity in science is now raised to something of a tropism. This does not impede our will to predict, if not the exact events, at least the short–term trends in the disciplines we live and breathe, and to point at the (subjective) glaring chances for a bright future. This volume is a clear example of the need that any living scientific discipline has for constant regrouping and redirection, in a never–ending process of consolidating results and finding new paths. In this contribution we will try and focus on a number of areas of fuzzy logic and, by extension, in the whole word of uncertainty, where (in our opinion) a number of interest…
Adaptive type-2 fuzzy control of non-linear systems
2009
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 w…
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…
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…
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.
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…
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.
An Intelligent Car Driver for safe Navigation with Fuzzy Obstacle Avoidance.
2009
In order to respond effectively to the environment uncertainties, autonomous vehicles are generally equipped with sensors. The proposed car guidance system is equipped with an intelligent controller, based on fuzzy logic, which calculates the speed and wheels orientation in order to follow a path while it is avoiding unknown obstacles. Better fluidity of driving are obtained using future-path, car dimension and car position prevision. Vehicle symmetries also speed-up and simplify the guidance system reducing the inputs and the rules numbers.