Controlling parameters proportional integral derivative of DC motor using a gradient-based optimizer

Widi Aribowo, Reza Rahmadian, Mahendra Widyartono, Ayusta Lukita Wardani, Aditya Prapanca, Laith Abualigah


In this paper, a gradient-based optimizer (GBO) algorithm is presented to optimize the parameters of a proportional integral derivative (PID) controller in DC motor control. The GBO algorithm which mathematically models and mimics is inspired by the gradient-based Newton method. It was developed to address various optimization issues. To determine the performance of the proposed method, a comparison method with the ant colony optimization (ACO) method. It was compared using the integral of time multiplied absolute error (ITAE). They are most popularly used in the literature. From the test results, the proposed method is promising and has better effectiveness. The proposed method, namely GBO-PID, shows the best performance.


artificial intelligence; DC motor; gradient-based optimizer; metaheuristic; proportional integral derivative

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