<p><span>Direct-current (DC) motor is a commonly used motor; its speed is directly affected by applying mechanical load. This paper proposes the design of wide speed-load range controller for a direct-current (DC) shunt motor based on proportional–integral–derivative (PID controller) with genetic system for controller parameters adjusting. The genetic based PID controller is simulated by using Matlab software package and tested with different sudden load values and different working speeds. A present control loop contains the suggested PID controller also Pulse-Width-Modulation PWM generator and H-bridge inverter. With the genetic system enhancement to parameters of developed PID controller, the results demonstration that this controller has great impact to preserve the profiles of the motor speed and produced torque after applied sudden load, and its intensification the motor performance at different speed and load conditions.</span></p>

The Induction Motors (IM) speed widely influenced due to various motor loading conditions. When the load is apply the motor speed is reduce from the reference speed. This work present Matlab simulation of a Proportional Integral (PI) controller incorporating with Neural Network for IM speed controls. The motor speed response profile under this control is improved and still constant at the point of load applied. Also this controller stilled operates efficiently at wide range of operating frequency when compared with traditional PI controller.

One of the most often utilized types of direct current (DC) motors in both the industrial and automotive sectors are brushless DC motors (BLDC). This research presents a comparative analysis on brushless DC motor speed management. A mathematical model of the BLDC motor is developed using MATLAB/Simulink, and its speed is tested using three alternative controller types. The first controller is a traditional proportional integral derivative (PID) controller for BLDC motor speed control. The second controller used the particle swarm optimization (PSO) approach with PID which give the best response for BLDC motor speed. The PID controller in the third method based on neural network also give best reaction on motor speed. Finally, comparison made in speed and torque profiles by using sudden changes in speed and load torque under the three proposed methods. The results show when using first controller the speed rise to 1,526 r.p.m and drop to 1,400 r.p.m at the test conditions. These oscillations will disappear when using the second and third controller.

The doubly fed induction generator (DFIG) systems feature a significant amount of free power capacity that may be used for reactive power adjustment when they are put into practical use. This change, which is occasionally overlooked, is a significant one. Using DFIG systems for wind turbines (WT), this paper explored strategies for reducing and using reactive power. In order to investigate the power characteristic and how it is regulated in DFIG systems, a mathematical model for the steady-state performance of DFIG WT has been developed and presented. Here is a detailed derivation of the limiting range of DFIG's reactive power capacity as well as the physical constraints on reactive power output. The distribution of the DFIG WT at a distribution network's end is demonstrated by a simulation example. Within this simulation, reactive power management strategy, load fluctuation, and the change in wind speed are all taken into consideration. Due to the possibility of a rise in the voltage at the access point, can concluded that both acceptable and efficient to use DFIG WT's reactive power capabilities as an additional continuous reactive power source for effectiveness.