Speed control for unmanned mining trucks based on frequency-domain energy shaping and dynamic co-optimization

Area of Science:

• Mechanical Engineering
• Control Systems Engineering
• Vibration Analysis

Background:

• Speed-command-induced torsional vibration is a major cause of drivetrain fatigue failure in unmanned mining trucks.
• Existing methods often fail to address vibration at its source, leading to persistent component wear.

Purpose of the Study:

• To develop a frequency-domain energy shaping and co-optimization framework to suppress torsional vibration at its source.
• To link speed command spectrum with system modal characteristics for effective vibration mitigation.

Main Methods:

• A three-metric system (excitation energy, residual vibration, acceleration duration) was used for joint optimization of speed profile and controller parameters.
• The Non-dominated Sorting Genetic Algorithm III (NSGA-III) was employed to generate a Pareto-optimal set for vibration suppression-mobility trade-off.
• Hardware-in-the-loop experiments were conducted to validate the proposed framework.

Main Results:

• The proposed method reduced torsional vibration by 91.5% compared to trapezoidal strategies and 80.4% compared to active-damping strategies.
• Significant mitigation of gear fatigue damage was observed.
• Robustness tests demonstrated strong adaptability with online computation below 0.06 ms.

Conclusions:

• The developed framework effectively suppresses torsional vibration at its source in unmanned mining trucks.
• This approach offers a transferable solution for command-induced vibration suppression in electromechanical systems.
• The method significantly enhances drivetrain durability and reduces maintenance needs.