The implementation of conventional DTC in Induction Motor drives consisting of PI torque controller suffers from complex tuning and Overshoot problems. One of the various methods to tackle this problem is implementation of intelligent controllers like neuro fuzzy-based controller This paper presents the simulation and analysis of a Neuro fuzzy-based torque controller for DTC of Induction motor ...

In this paper, Neuro-Fuzzy based Fuzzy Subtractive Clustering Method (FSCM) and Self Tuning Fuzzy PD-like Controller (STFPDC) were used to solve non-linearity and trajectory problems of pitch AND yaw angles of Twin Rotor MIMO system (TRMS). The control objective is to make the beams of TRMS reach a desired position quickly and accurately. The proposed method could achieve control objectives wit...

Navigation of multiple mobile robots using neuro-fuzzy controller has been discussed in this paper. In neuro-fuzzy controller the output from the neural network is fed as an input to fuzzy controller and the final outputs from the fuzzy controller are used for motion control of robots. The inputs to the neural network are obtained from the robot sensors (such as left, front, right obstacle dist...

Abstract A dc-dc power converter is difficult to control due to its non-linearities and parameter uncertainties. To tackle the problem, a neuro-fuzzy controller is proposed. The controller utilizes the error voltage and the change of error voltage as inputs, and outputs the duty cycle of the PWM switch for controlling the converter. Instead of relying on expert knowledge, some heuristic rules a...

The presented control scheme utilizes Adaptive Neuro Fuzzy Inference System (ANFIS) controller to track rotational speed of a reference engine and disturbance rejection during engine idling. To evaluate the performance of the controller a model of the system is developed and simulation results are presented. It is shown that the ANFIS controller is suitable for control systems with large time d...

This paper describes a self-tuning Neuro-fuzzy Controller by Genetic Algorithm (NFCGA) applied to a coupled-tank fluid level control. The controller use a simplified fuzzy algorithm which based on the Radial Basis Function neural network (RBF). Genetic Algorithm (GA) is used to tune simultaneously all the parameters of controller from a random state. A plant model is used initially to tune the ...

In this work neural and neuro-fuzzy controllers are developed for the inverters of Uninterruptible Power Supplies (UPS) to improve their transient response and adaptability to various loads. Idealized load-currentfeedback controller is built to obtain example patterns for training the networks. Example patterns under various loading conditions are used in the off-line training of the selected n...

A speed sensorless neuro-fuzzy controller is proposed for brush type DC motors. The actual speed of the DC machine is estimated using a feed-forward neural network. The inputs of the neural network are the armature current and voltage of the DC machine and their changes in time. Because DC machines are usually fed by 4-quadrant chopper, the measured armature voltage and current contains higher ...

As demand for high quality transmission increases, improving spectrum efficiency and error performance in wireless communication systems are important. OFDM is a multi-carrier modulation technique with densely spaced sub-carriers that has gained a lot of popularity among the broadband community in the last few years. One of the promising approaches to next generation communication systems are a...

The design of Automatic Generation Control (AGC) system plays a vital role in automation of power system. This paper proposes Hybrid Neuro Fuzzy (HNF) approach for AGC of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The advantage of proposed controller is that it can handle the system non-linearities and at the same time the pro...