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Vehicle Suspension System Uncertainty Modeling, Control and Performance Evaluations

This research investigates uncertain vehicle quarter suspension dynamics and associated performances for multiplicative, additive, quotient, and inverse dynamical uncertainty model descriptions. The uncertain system models consider the variation on its sprung mass range as the source of uncertainty, resulting in different passenger comfort levels and implying superior dynamical modeling and optimization frameworks. The proposed robust system framework considers four uncertain dynamical descriptions and utilizes the corresponding Linear Fractional Transformations to achieve the robust performance in terms of steady-state tracking for superior passenger comfort levels and acceptable actuator actions for practical operations under norm-bounded uncertainty. The modeling and control synthesis simulations verify the close relationship between the suspension system uncertain dynamical characterization and superior comfort levels and identifies the optimal uncertainty description.