Simulation reveals that genetic algorithm-optimized fuzzy PID control reduces overshoot to 5% in paving operations, indicating significant advancements in dynamic performance and adaptability.
The control precision of the paver screed directly affects the quality of road surface construction, yet traditional Proportional-Integral-Derivative (PID) control struggles to adapt to complex working conditions. While fuzzy PID control improves adaptability, its parameters rely on empirical settings, leading to subjectivity and limited optimization potential. To address this, this study proposes a genetic algorithm-optimized fuzzy PID control method, which automatically adjusts controller parameters through intelligent algorithms. Simulation results demonstrate that the optimized system reduces overshoot to 5%, a significant improvement over traditional PID (25%) and fuzzy PID (20%), while settling time is shortened by 37.5%. This method effectively enhances dynamic performance and anti-interference capability, offering a new approach for high-precision paving operations.
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Yang et al. (2025) studied this question.
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