Brushless DC (BLDC) motors are commonly used in applications that require high reliability, high efficiency and high power-to-volume ratio such as industrial automations, manufacturing, robotics and aerospace. The speed of a brushless dc motor can be controlled in a closed loop by measuring the actual speed of the motor.PI (Proportional Integral), PID (Proportional Integral Derivative) and fuzz...

1PG student, Dept. of EEE, Andhra University (A), Visakhapatnam, India 2Professor, Dept. of EEE, Andhra University (A), Visakhapatnam, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract In this paper we summarized the design and implementation of fuzzy logic controller to solve automatic powe...

A hybrid model is designed by combining the genetic algorithm (GA), radial basis function neural network (RBF-NN) and Sugeno fuzzy logic to determine the optimal parameters of a proportional-integralderivative (PID) controller. Our approach used the rule base of the Sugeno fuzzy system and fuzzy PID controller of the automatic voltage regulator (AVR) to improve the system sensitive response. Th...

Autonomous driving of mobile robot is important in various working environment. For its autonomous driving, mobile robot utilized ultrasonic sensor to detect obstacles and avoid them. Also, there has been researched on supplementing function of avoiding crash by using control methods based on adoption of intellectual system. This research has designed type-2 fuzzy selftuning PID controller whic...

In this paper we propose a parallel structure of I-P-D (Integral minus Proportional minus Derivative) type fuzzy controller based on the conventional PID control theory, used to control the speed of DC motor. The conventional PID controller exhibit poor performance when applied to DC motor, it fails to perform satisfactory under parameter variation or load changes. The parallel I-P-D type fuzzy...

In this paper, a new improved Differential Search Algorithm optimization approach is proposed and successfully applied to the design and tuning of a PID-type Fuzzy Logic Controller. The scaling factors tuning problem of the Fuzzy Logic Controller structure is formulated and systematically resolved, using the improved constrained Differential Search Algorithm-based method. A comparison, with the...

A concept called the decomposition of multivariable control rules is presented. Fuzzy control is the application of the compositional rule of inference and it is shown how the inference of the rule base with complex rules can be reduced to the inference of a number of rule bases with simple rules. A fuzzy logic based controller is applied to a simple magnetic suspension system. The controller h...

The popular linear PID controller is mostly e3ective for linear or nearly linear control problems. Nonlinear PID controllers, however, are needed in order to satisfactorily control (highly) nonlinear plants, time-varying plants, or plants with signi5cant time delay. This paper extends our previous papers in which we show rigorously that some fuzzy controllers are actually nonlinear PI, PD, and ...

This paper discusses the performance of various intelligent control schemes in extracting maximum wind power using doubly fed induction generator (DFIG). Intelligent control scheme such as fuzzy, neuro-fuzzy, and genetic algorithm based fuzzy controllers are applied for pitch control of DFIG based wind generation system. Wind generation system with eight numbers of identical 1.5MW wind generato...

Analytical structure for a fuzzy PID controller is introduced by employing two fuzzy sets for each of the three input variables and four fuzzy sets for the output variable. This structure is derived via left and right trapezoidal membership functions for inputs, trapezoidal membership functions for output, algebraic product triangular norm, bounded sum triangular co-norm, Mamdani minimum infere...