This study focuses on multi-objective optimization of the PID controllers for optimal speed control for an isolated steam turbine. In complex operations, optimal tuning plays an imperative role in maintaining the product quality and process safety. This study focuses on the comparison of the optimal PID tuning using Multi-objective Genetic Algorithm (NSGA-II) against normal genetic algorithm an...

Frequency deviation is a one of major technical issue of a interconnected power system. In this paper an optimized Proportional-Integral-Derivative (PID) controller ios proposed for controlling the frequency deviation. To optimize the gain values of controller, the Adaptive Particle Swarm Optimization (APSO) algorithm is utilized. Tuning of controllers is done in order to get the gain values or...

This Paper presents a comparative study of Genetic Algorithm method (GA) and Particle swarm optimization (PSO) method to determine the optimal proportional-integral (PI) and proportional-integral-derivative (PID) controller parameters, for speed control of a Field Oriented Control (FOC) induction motor. The FOC induction motor has been modeled in MATLAB (SIMULINK); the GA and PSO algorithm has ...