The Linear Quadratic Gaussian (LQG) technique has been applied to the design of active vehicle suspensions (AVSs) for improving ride quality and handling performance. LQG-based AVSs have achieved good performance if an accurate vehicle model is available. However, these AVSs exhibit poor robustness when the vehicle model is not accurate and vehicle operating conditions vary. The H control theory, rooted in the LQG technique, specifically targets on robustness issues on models with parametric uncertainties and un-modelled dynamics. In this research, an AVS is designed using the H loop-shaping control, design optimization, and parallel computing techniques. The resulting AVS is compared against the baseline design through numerical simulations.

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