In this paper, an adaptive neuro fuzzy interference (ANFIS) based hybrid field oriented speed controlling of an induction motor is proposed. The proposed hybrid field oriented speed controller results attractive performance of induction motor with the potential features of both Artificial Neural network (ANN) and Fuzzy Logic Controller (FLC). In this topology the Artificial Neural Network (ANN)...

This paper presents two new intelligent methods to linearize the Multi-Carrier Power Amplifiers (MCPA). One of the them is based on the Neuro-Fuzzy controller while the other uses two small neural networks as a polar predistorter. Neuro-Fuzzy controllers are not model based, and hence, have ability to control the nonlinear systems with undetermined parameters. Both methods are adaptive, low com...

A decrease in the birthrate and aging are progressing in Japan and several countries. In that society, it is important that physically weak persons such as elderly persons are able to take care of themselves. We have been developing exoskeletal robots for human (especially for physically weak persons) motion support. In this study, the controller controls the angular position and impedance of t...

In this paper, a neuro-fuzzy based Call Admission Control (CAC) algorithm for ATM networks has been simulated. The algorithm presented employs neuro-fuzzy approach to calculate the bandwidth require to support multimedia traffic with QoS requirements. The neuro-fuzzy based CAC calculates bandwidth required per call using measurements of the traffic via its count-process, instead of relying on s...

This paper studies the evolutionary design of a fuzzy P+ID controller for an actual pneumatic muscle actuator system. The control of pneumatic muscles is a challenging problem because of their high degree of nonlinearity, time-varying parameters, and uncertainty. A fuzzy P+ID controller is constructed using an incremental fuzzy logic controller in place of the proportional term in a conventiona...

An energy efficient pipelined architecture is proposed for multi-core object recognition processor. The proposed neuro-fuzzy controller and intelligent estimation of the workload of input video stream enable seamless pipelined operation of the 3 object recognition tasks. The neuro-fuzzy controller extracts the fine-grained region-of-interest, and its task pipelining achieves 60.6fps, 5.8x highe...

In this paper, a Neuro-Predictive (NP) controller is designed and implemented on a highly non-linear system, a model helicopter in a constrained situation. It is observed that the closed loop system with the NP controller has a significant overshoot and a long settling time in comparison to the same system with an existing fuzzy controller. In order to improve the undesired system performance, ...

The presented control scheme utilizes Adaptive Neuro Fuzzy Inference System (ANFIS) controller to track a reference engine rotational speed and disturbance rejection during engine idling. To evaluate the performance of the controller a model of the engine is simulated and simulation results presented. ANFIS implements a first order Sugeno-style fuzzy system. It is a method for tuning an existin...

This paper presents an original variable gain PI (VGPI) controller for speed control of a direct torque neuro fuzzy controlled (DTNFC) induction motor drive. First, a VGPI speed controller is designed to replace the classical PI controller in a conventional direct torque controlled induction motor drive. Its simulated performances are then compared to those of a classical PI controller. Then, a...

A fuzzy controller is suited to control Antilock Brake System (ABS) however time complexity of fuzzy controller is high order. Problem Solution Data Structure (PSDS) has been introduced as a data-oriented model of fuzzy controller to reduce the response time. Locally learning of PSDS controller has been left as an open issue. Fuzzy Learning Mechanism (FLM) has been introduced by using fuzzy inf...