Today, DC motors is still being used globally due to their easy speed controllability. In this article, an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is designed for DC motors. The main purpose of performing such task is to reduce the DC motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...

Generally, the greatest difficulty encountered when designing a fuzzy sliding mode controller FSMC or an adaptive fuzzy sliding mode controller AFSMC capable of rapidly and efficiently controlling complex and nonlinear systems is how to select the most appropriate initial values for the parameter vector. In this paper, we describe a method of stability analysis for a GA-based reference adaptive...

The ever-growing use of various vehicles for transportation, on the one hand, and the statistics ofsoaring road accidents resulting from human error, on the other hand, reminds us of the necessity toconduct more extensive research on the design, manufacturing and control of driver-less intelligentvehicles. For the automatic control of an autonomous vehicle, we need its dynamic...

Recent medical studies have investigated the importance of enteral feeding and the use of feeding pumps for recovering patients unable to feed themselves or gain nourishment and nutrients by natural means. The most of enteral feeding system uses a peristaltic tube pump. A peristaltic pump is a form of positive displacement pump in which a flexible tube is progressively squeezed externally to al...

This paper proposes a fuzzy PID control method for deburring industrial robots. The adaptive fuzzy PID controller relates to the trajectory and joint angular parameters of the end-effector on a robot. The PID controller parameters update online at each sampling time to guarantee trajectory accuracy of the end-effector. The simulation of the fuzzy PID control is provided based on the 6-DOF debur...

This paper presents a novel approach to control the speed of BLDC motor by using PID, Fuzzy, Neural Network and Anti-windup Controllers. The PID controllers is set to optimize the motor parameters such as rise time, peak time, Maximum peak overshoot and Settling time. The fuzzy controller adopts fuzzy logic to retune the PID parameters. Based on the mathematical model of BLDC Motor, novel adapt...

This paper proposes an adaptive TSK-type fuzzy network control (ATFNC) system for synchronization of a coupled nonlinear chaotic system. The design of the proposed ATFNC system is comprised of a neural controller and a fuzzy compensator. The neural controller uses a Takagi-Sugeno-Kang (TSK)-type fuzzy neural network (TFNN) to online mimic an ideal controller and the fuzzy compensator is designe...

Active filters are widely employed in distribution system to reduce the harmonics produced by non-linear loads result in voltage distortion and leads to various power quality problems. In this work the simulation study of a Adaptive hysteresis based fuzzy logic controlled shunt active power filter capable of reducing the total harmonic distortion i s presented. The advantage of fuzzy control is...

Abstract. A Fuzzy-PID controller is designed for tracing reference cutting forces in grinding by integrating a high performance fuzzy controller and an easy to use PID controller. When the error of the grinding force is large, in order to respond quickly, the fuzzy controller with a self-tuning factor is adopted and the Max-Proc strategy is also used. This will be good for fuzzy reasoning. If t...

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...