Fuzzy logic is a modeling method intended to formalize a mathematical approach to deal with these complex or ill-defined systems and is, therefore, a relatively new mathematical paradigm. Its basis is a consideration of overlapping sets and the definition of operators to manipulate these sets. According to Zadeh and Mamdani, fuzzy logic could be used to develop operational automatic control sys...

Fuzzy logic control systems are structured numerical estimators. They combine both the numerical process and human like reasoning. Neural networks are numerical trainable dynamical systems that are able to emulate human brain functions; their connectionist structure can be used to find the proper parameters and structures that resemble human thinking rules for fuzzy logic controllers. Generally...

There are two possible ways for integrating fuzzy logic and evolutionary algorithms. The first one involves the application of evolutionary algorithms for solving optimization and search problems related with fuzzy systems, obtaining genetic fuzzy systems. The second one concerns the use of fuzzy tools and fuzzy logic-based techniques for modelling different evolutionary algorithm components an...

Fuzzy logic is a natural basis for modelling and solving problems involving imprecise knowledge and continuous systems. Unfortunately, fuzzy logic systems are invariably static (once created they do not change) and subjective (the creator imparts their beliefs on the system). In this paper we address the question of whether systems based on fuzzy logic can effectively adapt themselves to dynami...

Load balancing in distributed computer systems is the process of redistributing the work load among processors in the system to improve system performance. Most of previous research in using fuzzy logic for the purpose of load balancing has only concentrated in utilizing fuzzy logic concepts in describing processors load and tasks execution length. The responsibility of the fuzzy-based load bal...

Fuzzy systems, including fuzzy set theory and fuzzy logic, provide a rich and meaningful improvement, or extension of conventional logic. The mathematics generated by this theory is consistent, and fuzzy set theory may be seen as a generalisation of classic set theory. Applications in soil science, which may be generated from, or adapted to fuzzy set theory and fuzzy logic, are wide-ranging: nu...

A backlash compensator is designed for nonlinear systems using the fuzzy logic. The classification property of fuzzy logic systems makes them a natural candidate for the rejection of errors induced by the backlash, which has regions in which it behaves differently. A tuning algorithm is given for the fuzzy logic parameters, so that the backlash compensation scheme becomes adaptive, guaranteeing...

Adaptive fuzzy logic control systems with Gaussian membership functions are described. A systematic simulation study of 'dynamic focusing of awareness' in fuzzy logic control systems is provided. This study shows how the final steady-state values of the membership functions change in response to varying initial membership functions, changing desired trajectory, and varying system nonlinearities...