this paper presents an intelligent speed control system based on fuzzy logic for a voltage source PWM inverterfed indirect vector controlled induction motor drive. Traditional indirect vector control system of induction motor introduces conventional PI regulator in outer speed loop; it is proved that the low precision of the speed regulator debases the performance of the whole system. To overco...

This paper presents a consolidated view of the computational intelligence used in the natural language steganalysis. In order to understand the human intelligence on natural language, four major computational intelligence methods have been identified. They are bayesian, fuzzy logic, neural network, and genetic algorithm. This paper also presents a measurement tool to measure the natural languag...

A method for response integration in modular neural networks with type-2 fuzzy logic for biometric systems p. 5 Evolving type-2 fuzzy logic controllers for autonomous mobile robots p. 16 Adaptive type-2 fuzzy logic for intelligent home environment p. 26 Interval type-1 non-singleton type-2 TSK fuzzy logic systems using the hybrid training method RLS-BP p. 36 An efficient computational method to...

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...

This paper presents an intelligent speed control system based on fuzzy logic for a voltage source PWM inverter-fed indirect vector controlled induction motor drive. Traditional indirect vector control system of induction motor introduces conventional PI regulator in outer speed loop; it is proved that the low precision of the speed regulator debases the performance of the whole system. To overc...

In this thesis, an intelligent fuzzy logic system using genetic algorithms for the prediction and modelling of interest rates is developed. The proposed system uses a Hierarchical Fuzzy Logic system in which a genetic algorithm is used as a training method for learning the fuzzy rules knowledge bases. A fuzzy logic system is developed to model and predict three month quarterly interest rate flu...

This paper presents a fuzzy neural network approach to virtual product design. Contemporary design process requires the development of a new computational intelligent methodology that involves intelligent integration of design, analysis and evaluation, simulation and optimization in a virtual environment. In the paper, a soft-computing framework is developed for engineering design based on a hy...

In this paper, a worm-like micro robot designed for inpipe application with intelligent active force control (AFC) capability is modelled and simulated. The motion of the micro robot is based on an impact drive mechanism (IDM) that is actuated using piezoelectric device. The trajectory tracking performance of the modelled micro robot is initially experimented via a conventional proportionalinte...

This paper describes a student design workshop conducted in the Electrical and Computer Engineering (ECE) Department at the University of Minnesota Duluth (UMD) in which students implemented microcontroller applications using the principles of Fuzzy Logic as contained in the features of the MC68HC12 microcontroller. This workshop provided students with a unique opportunity to merge their academ...

This paper presents a comprehensive review of the work done during 1990–2008 in the application of intelligent techniques to solve software engineering (SE) problems. The review is categorised according to the type of intelligent technique applied viz. (1) neural networks (NNs), (2) fuzzy logic, (3) genetic algorithm, (4) decision tree, (5) case base reasoning and (6) other techniques subsuming...