To enhance riding comfort for drivers of heavy-duty vehicles, this paper introduces a novel adaptive prescribed performance control (APPC) for active seat suspension systems. The model incorporates dynamic friction and hysteresis damping effects to capture the complex behavior of the seat suspension. The accuracy of the proposed model is validated through experimental data. The controller utilizes a prescribed performance function (PPF) to regulate the dynamic response of the system, combined with an adaptive backstepping control (ABC) method to account for system uncertainties, such as variations in driver weight, friction, suspension stiffness, and damping coefficients. A set of parameter estimators, governed by innovative adaptive laws, compensates for estimation errors. Furthermore, the stability of the controlled system is rigorously demonstrated. Both simulation and experimental tests, including bump and random excitation tests, are conducted to assess the controller performance in both time and frequency domains. The results confirm that the proposed controller effectively mitigates vibrations in the driver–seat system and demonstrates robustness against system uncertainties.

An oil filter is a necessary and significant part of many manufacturing processes and equipment. Unlike the structural design and filter material selection, the particle movement in the filter during filtration is the fundamental factor influencing the filter’s performance, but this has not attracted enough attention. Due to the small size and large number of particles in the filter, it is difficult to monitor every particle’s movement. Therefore, this work used a hydraulic oil filter as a case study. Computational Fluid Dynamics (CFD) was coupled with the Discrete Phase Model (DPM) to investigate the particle motion in the filter. A filter boundary function was programmed to simulate the filter cartridge zone. The effects of inlet velocity and oil temperature/viscosity on the particle movement and filtration performance were studied. The results showed that a low-velocity zone existed and trapped some contaminant particles, particularly for particles with large Stokes numbers. The results also demonstrated that increased temperature induced an apparent reduction in filtering efficiency within the first 1.8 s from 0.61 to 0.49 when the temperature increased from 15 °C to 70 °C for 25 μm particles.