The current study addresses the impact of the optimized controller to load frequency control (LFC) problem. The proportional-integral-derivative (PID) parameters is determined for both single area and two area control system using genetic algorithms (GA), Particle swarm optimization (PSO), and grey wolf optimization techniques (GWO). The LFC is a stochastic problem due to the load variations and changing the system operating conditions. This results in failing the conventional controller to adapt the LFC in case of implementing the conventional PID. So that, implementing optimized, the PID controller parameters using GA, PSO, and GWO. The technique is used for single area system as well two-area system. The results show the accuracy and robustness of implementing the optimized controller parameters. MATLAB/Simulink is used to solve the system equations. The suggested optimized controller shows fast response with better control quality in compared with conventional controller.

An Intelligent Lighting Control System (ILCS) was proposed and designed by considering ergonomic setting and energy efficiency. The integration of CompactRIO and National Instrument Laboratory Virtual Instrument Engineering Workbench (NI LabVIEW) 2012 as a platform to design an interactive Graphical User Interface (GUI) as well as integrating components within the system. The proportional controller programmed in NI LabVIEW provides autonomous dimmer control and adjustment of the light-emitting diode (LED conducted shows the developed system capable of contro based on the luminance set point. Moreover, the result also showed the average power saving of up to 33% compared to normal use. However, several modifications and improvements are desired before the system could be app