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G. K. Voronovskiy, K. V. Makhotilo, S. N. Petrashev and S. A. Sergeev, “Genetic Algorithms, Artificial Neuron Networks and Problems of Virtual Reality,” Basis, Kharkov, 1997.

has been cited by the following article:

• TITLE: Particle Swarm Optimization (PSO) Based Turbine Control

  AUTHORS: Ali Tarique, Hossam A. Gabbar

  KEYWORDS: PSO; PID Controller; GA; Optimization

  JOURNAL NAME: Intelligent Control and Automation, Vol.4 No.2, May 24, 2013

  ABSTRACT: The steam turbine control system is strongly non-linear in all operating conditions. Proportional-Integral-Derivative (PID) controller that is currently used in control systems of many types of equipment is not considered highly precision for turbine speed control system. A fine tuning of the PID controller by some optimization technique is a desired objective to maintain the precise speed of the turbine in a wide range of operating conditions. This Paper evaluates the feasibility of the use of Particle Swarm Optimization (PSO) method for determining the optimal Proportional-Integral-Derivative (PID) controller parameters for steam turbine control. The turbine speed control is modelled in SimulinkTM with PID controller and the PSO algorithm is implemented in MATLAB to optimize the PID function. The PSO optimization technique is also compared with Genetic Algorithm (GA) and it is validated that PSO based controller is more efficient in reducing the steady-states error; settling time, rise time, and overshoot limit in speed control of the steam turbine control.