Ball and beam system is an experimental set for control system design that the position of the ball on a beam is changed with respect to the reference direction by changing the angle of the beam. The PID controller is applied to this problem. The performance of this controller is depended on the controller parameter values. On this study three optimization algorithms; Genetic Algorithm, Particle Swarm Optimization and Differential Evolution are applied to the tuning problem to get optimal parameters. The mathematical model of the system is evaluated by comparing the outputs from both real system and the simulation environment. In addition, the performance of these optimization algorithms with respect to the decision space boundaries is investigated by defining four difference ranges. The implementations are demonstrated on both the simulation environment and the ball and beam system hardware.

Keywords - ball and beam system; PID controller; implementation; optimization; genetic algorithm; particle swaarm optimization; differential evolution

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