Abstract

Stability, resilience, and optimal performance are critical goals in the field of process control, particularly in the design of proportional-integral-derivative (PID) controllers for direct current (DC) motors. To identify the most suitable PID controller parameters for various industrial applications, it is essential to evaluate the effectiveness of different tuning approaches. This study considers three PID controller design methods: the traditional Ziegler–Nichols (ZN) technique, the particle swarm optimization (PSO) algorithm, and a novel strategy based on the random forest (RF) algorithm. The ZN method provides a heuristic-based tuning approach derived from the dynamic response of the DC motor. The PSO algorithm employs a metaheuristic optimization process that iteratively adjusts PID parameters to minimize a predefined objective function. In addition, this study explores the use of the RF technique to automatically estimate and optimize PID controller parameters using historical DC motor performance data. Simulation results obtained using MATLAB demonstrate that the RF-based tuning approach outperforms both the ZN- and PSO-based controllers. Specifically, the RF-tuned PID controller achieves the best rise time (Tr) of 0.0084 s and settling time (Ts) of 0.0227 s, with no maximum peak overshoot (Mp) and negligible error indices, including an integral of squared error (ISE) of 0.00218, an integral of absolute error (IAE) of 0.1102, and an integral of time-weighted absolute error (ITAE) of 0.0489. Furthermore, convergence analysis confirms the ability of the RF approach to consistently attain lower cost function values (J = 0.010) across all trials, achieving a 100% success rate and demonstrating strong robustness and repeatability.

Keywords

PID controller, DC motor control, Random forest, Particle swarm optimization, Ziegler–nichols tuning, MATLAB simulation.

Cite this article

P A, N L, A N, K R. Design and intelligent tuning of a proportional–integral–derivative controller for an armature-controlled DC motor. International Journal of Advanced Technology and Engineering Exploration. 2026;13(134):85-101. DOI : 10.19101/IJATEE.2025.121220008

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