PID Controller Optimization for Rotational Inverted Pendulum System Using Particle Swarm Optimization and Differential Evolution Algorithms
This paper presents stochastic search techniques, including Particle Swarm Optimization (PSO), Constriction Coefficient Particle Swarm Optimization (CPSO) and Differential Evolution (DE) algorithms for determining optimal Proportional-Integral-Derivative (PID) controller parameters attached to the Rotational Inverted Pendulum (RIP) system. This paper demonstrates in detail how to employ these proposed algorithms to optimize the performance index for balancing the pendulum in vertical-upright position. The efficiency of these intelligent strategies to tune PID gains is compared and evaluated based on the time response performance. The simulation results clearly demonstrate superior features of proposed tuning approaches, including easy implementation, and good computational efficiency. The overall results have validated that CPSO method yields better performance in control action compared to PSO and DE. The proposed approaches could generally be considered as an encouraging way for control of nonlinear industrial plants.
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