Stabilization of inverted pendulum system using particle swarm optimization

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. This paper presents an artificial intelligence (AI) method of particle swarm optimization (PSO) algorithm for tuning the optimal PID controller parameters for industrial process. PSO is a technique used to explore the search space of a given problem to find the settings or parameters required to maximize a particular objective. The focus will be on the application of the PSO into one of the popular problem setups in the engineering application area of control systems, which is called the inverted pendulum. This approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency over the conventional methods. The controller is obtained and validated by simulation; it's implemented to control the pendulum-cart system.

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