This paper presents an application of adaptive neuro-fuzzy (ANFIS) control for switched reluctance motor (SRM) speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed cont...

In this paper, a Proportional-Derivative and Integral (PD-I) type Fuzzy-Neural Network Controller (FNNC) based on Sugeno fuzzy model is proposed for brushless DC drives to achieve satisfied performance under steady state and transient conditions. The proposed FNNC uses the speed error, change of error and the error integral as inputs. While the PD-FNNC is activated in transient states, the PI-F...

Abstract— This paper presents a comparative analysis of speed control in brushless DC motor (BLDC motor) using proportional-integral (PI) controller and Fuzzy logic controller (FLC). The controllers were analyzed under no load and loaded condition of the motor. The various parameters such as settling time, peak over shoot, steady state error, and mean square error were calculated and compared f...

This paper presents a detailed comparison between a conventional PI controller and a variable structure controller based on a fuzzy sliding mode strategy used for speed control in direct torque control induction motor drive. Genetic algorithms are used to tune the PI controller gains to ensure optimal performance. The performance of the two controllers are investigated and compared for differen...

The conventional Proportional-Integral (PI) speed control has been widely used in industrial motor controls due to its capabilities in controlling linear plants. However, motor behaves as non-linear plant where the PI speed control may not be able to provide precise speed responses. With the fast growing of artificial intelligent in motor controls, the fuzzy logic and Adaptive Network Fuzzy Inf...

This paper studies the control of a pH process by using a neuro fuzzy controller with gain scheduling. As the process to be controlled is highly non-linear the PI-type fuzzy controller that will be used generally is not able to control the system adequately. For this, a very simple feedforward neural network trained on-line, is put at the output of the PI-type fuzzy controller in order to calcu...

The Particle Swarm Optimized (PSO) fuzzy controller has been proposed for indirect vector control of induction motor. In this proposed scheme a Neutral Point Clamped (NPC) multilevel inverter is used and hysteresis current control technique has been adopted for switching the IGBTs. A Mamdani type fuzzy controller is used in place of conventional PI controller. To ensure better performance of fu...

Fuzzy logic or fuzzy set theory is recently getting increasing emphasis in process control applications. This paper presents an application of fuzzy logic to control the speed of a synchronous machine (SM). Based on the analysis of the SM transient response and fuzzy logic, a fuzzy controller is developed. The fuzzy controller generates the variations of the reference current vector of the SM s...