Performance Study of Enhanced Non-Linear PID Control Applied on Brushless DC Motor

Brushless DC Motor Fuzzy PID Control System and Simulation

For digital model of brushless DC motor, simulation models can be built in MATLAB / Simulink. Simulation parameters are selected parameters according to the actual system. The conventional PID control algorithm produce large overshoot and oscillation, we use fuzzy logic PID algorithm to response quickly and back the system overshoot to steady state, the steady state has a higher precision, fast...

Sensorless Control of a Brushless DC Motor

This paper uses a new position sensor less drive for brushless DC (BLDC) motors. In conventional sensor less control methods such as the back-EMF detection method, the performance is high only at a high speed range due to the fact that the magnitude of the back-EMF is dependent on the rotor speed. A solution is derived that estimates the rotor position by using an unknown input observer over a ...

Optimal Tuning of PID Controller for a Linear Brushless DC Motor using Particle Swarm Optimization Technique

This Paper presents a novel Cultural Algorithm based particle swarm optimization (PSO) technique which is intended to assist in converging to a accurate solution in the control of Linear Brushless Direct Current motor (LBLDC). With the novel PSO-based approach the optimal Proportional-Integral-Derivative (PID) controller parameters are deduced for efficient speed control of Linear Brushless DC ...

A PSO-Based Optimum Design of PID Controller for a Linear Brushless DC Motor

This Paper presents a particle swarm optimization (PSO) method for determining the optimal proportional-integralderivative (PID) controller parameters, for speed control of a linear brushless DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modelled in Simulink and...

AVR194: Brushless DC Motor Control using ATMega32M1