Automatic tuning of (PID)‎ controller using particle swarm optimization (PSO)‎ algorithm for steam engine speed Control (SESC)‎

Abstract EN

The proportional-integral-derivative (PID) controllers are the most popular controllers used in industry because of their remarkable effectiveness, simplicity of implementation and broad applicability.

However, tuning of these controllers is time consuming, not easy and generally lead to poor performance especially with non-linear systems.

This paper presents an artificial intelligence (AI) method of particle swarm optimization (PSO) algorithm for tuning the optimal (PID) controller parameters for steam engine speed control (SESC) system to achieve the mean objective which is the tracking between the reference speed and the output speed .This approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency over the conventional methods.

The PID conventional controller had been applied and results were compared with the automatic tuning PSO-PID for (SESC) using Simulink of Matlab .

Simulation results for the proposed method give optimum input/output tracking and the error equal zero without using the conventional solutions for standard engine control problems like cascade feedback gain and dither signal ,where in traditional tuning method of PID the tracking cannot achieve exactly without error, unless using conventional solutions.