Adaptive Bioinspired Preview Suspension Control With Constrained Velocity Planning for Autonomous Vehicles

Autonomous vehicles equipped with numerous advanced sensors are capable of obtaining road preview information, creating new opportunities for vehicle suspension systems. This article proposes a novel preview suspension control method from adaptive nonlinear control perspectives with less computational burden and is more realistic, unlike optimization-based works or existing linear state-space models-based results that neglected nonlinear terms. The X-shaped bio-inspired dynamics derived from animal or insect skeleton structures are introduced to reduce energy consumption by utilizing beneficial geometrical nonlinearities. Meanwhile, optimal velocity planning approach is investigated to balance vehicle passage time, vibration suppression, and longitudinal comfort by solving a multi-objective optimization problem with the aid of road preview information. Moreover, acceleration constraint reduces the search space and computing requirements, while ensuring planned velocity optimality. Simulation and experiment results are provided to demonstrate the effectiveness and advantages of the constructed energy-saving adaptive preview control framework with constrained velocity planning.

Automated summary

This article proposes a novel preview suspension control method from adaptive nonlinear control perspectives, which reduces computational burden and is more realistic compared to optimization-based works or existing linear state-space models-based results that neglected nonlinear terms. The X-shaped bio-inspired dynamics derived from animal or insect skeleton structures are introduced to reduce energy consumption utilizing beneficial geometrical nonlinearities. An optimal velocity planning approach is investigated to balance vehicle passage time, vibration suppression, and longitudinal comfort by solving a multi-objective optimization problem with the aid of road preview information. Acceleration constraint reduces search space and computing requirements while ensuring planned velocity optimality. Simulation and experiment results demonstrate the effectiveness and advantages of the constructed energy-saving adaptive preview control framework with constrained velocity planning.