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Proportional-integral-derivative (PID) controllers are a classical control algorithm that are still widely used owing to their simplicity and accuracy. However, tuning the three parameters is difficult. No methods have been known to determine the exact ideal combination of the P, I, and D gains. Moreover, controlling a system that contains dynamics changes over time using fixed parameters is difficult. A self-tuning neuro-PID controller is applied to a balloon robot for indoor entertainment to enhance its accuracy in following a target trajectory. Our experiment shows the effectiveness of the neuro-PID controller over conventional hand-tuned PID controller.

Self-Tuning Neuro-PID Controller for Indoor Entertainment Balloon Robot