Fuzzy-reasoning-based robust vibration controller for drivetrain mechanism with various control input updating timings

Abstract

For active vibration control of powertrain oscillations, the purpose of this research is to present a simple fuzzy-reasoning-based compensation strategy for a time-varying control cycle limitation of an actuator. A simplified drivetrain dynamics model is shown, and the simulation configuration with the control cycle limitation is constructed. A model predictive compensation using a sampled-data controller is employed to tackle the maximal phase delay of the control input due to the time-varying control cycle. The control input update timing, which is perturbed from that of the fixed periodical controller, is expressed as fuzzy sets such as “Approximately past step” and “Approximately future step”. Based on these fuzzy sets, the Tsukamoto-type fuzzy reasoning with only four intuitive rules can flexibly infer unknown control inputs updated at various timings. Simulation verifications demonstrate that the 2-norm of the vibration performance by the proposed method is reduced by more than 27.8% compared to other previous controllers. Moreover, it is revealed that the better transient performance can be maintained even with 10% plant parameter variations, indicating the high robustness of the proposed damping controller.