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To ensure comfort and longevity of vehicle components, it is important to suppress low-frequency transient vibrations in the powertrain. This study proposes a unique technique for active vibration control that incorporates six rules-based fuzzy logic compensation. The technique addresses changes in control periods of an actuator over time. Firstly, a model prediction technique is used with a sampled-data controller (SDC) to address the highest possible phase delay in the control input caused by the fluctuating control period. In addition, fuzzy sets are utilized to define the changing renewal timings of the control input, which are distinct from the regular timings used by the periodically operated SDC. These fuzzy sets are named &#x201C;Nearly previous timing&#x201D; and &#x201C;Nearly upcoming timing&#x201D;. This study employs six inference rules to achieve fuzzy compensation that resembles human intuition. These rules utilize output variables defined by linguistic fuzzy sets, such as &#x201C;Similar to commands from SDC&#x201D; and &#x201C;Very similar to commands from SDC&#x201D;, making the inference process more flexible. Due to the utilization of the fuzzy sets and periodic control signals provided by the SDC, it is possible to reasonably deduce unknown control inputs at various update timings. To evaluate the effectiveness of the control scheme, simulations and experiments are conducted using an actual test setup to investigate its damping performance. The experimental findings indicate that the new active damping technique effectively minimizes transient powertrain vibrations. Furthermore, comparative studies with previous control systems indicate the improved performance and robustness of the proposed approach.

Novel powertrain vibration controller with six rules-based fuzzy inference for time-fluctuated control period