Autonomous vehicles require sophisticated software controllers to maintain vehicle performance in the presence of vehicle faults. The test and evaluation of complex software controllers is a challenging task. The goal of this eeort is to apply machine learning techniques to the general problem of evaluating an intelligent controller for an autonomous vehicle. The approach involves subjecting a ...

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...

dear editor:    the rising importance of emotional intelligence gives a clear idea of the significant differences between men and women, since men and women are emotionally intelligent in different ways. understanding and appreciating such differences leads to the improvement of the existing relationships and to the establishment of new relationships in a satisfying manner.       one of the pri...

An alternative approach for intelligent tuning of a control loop will be presented in this paper. The objective is to design an algorithm which will tune the controller employing a neuro-fuzzy based algorithm. Structure and design method based on this approach will be explored, which include an adaptive network employed as building block, the backpropagation gradient method and least square est...

This paper presents an intelligent adaptive control system (IACS) using a recurrent functional-linkbased Petri fuzzy-neural-network (RFLPFNN) for induction motor (IM) servo drive to achieve high dynamic performance. The proposed IACS comprises a RFLPFNN controller and a robust controller. The RFLPFNN controller is used as the main tracking controller to mimic an optimal control law while the ro...

This thesis proposes an intelligent multiple-controller framework for complex systems that incorporates a fuzzy logic based switching and tuning supervisor along with a neural network based generalized learning model (GLM). The framework is designed for adaptive control of both Single-Input Single-Output (SISO) and MultiInput Multi-Output (MIMO) complex systems. The proposed methodology provide...

This paper proposes the use of machine learning techniques to build an efficient learner’s emotional transition diagram transition. For information Extraction tasks, we led an experimentation in which we exposed a group of 17 learners to a series of pictures from the International Affective Picture System (IAPS). Decision tree classifier has demonstrated the best ability to learn model structur...