Adaptive Backstepping Control for Nonlinear Vehicles With Guaranteed String Stability and Suppressed Cascade...

Area of Science:

• Control Systems Engineering
• Robotics
• Automotive Engineering

Background:

• Connected and automated vehicles (CAVs) have seen progress in platoon control.
• Existing methods often overlook the
• butterfly effect
• leading to unpredictable fluctuations in nonlinear platoons.
• Individual vehicle and string stability do not prevent uncomfortable velocity and acceleration variations.

Purpose of the Study:

• To propose a parallel error-fluctuation suppression control framework for CAV platoons.
• To address and mitigate the unpredictable
• butterfly effect
• in nonlinear vehicle platooning.
• To ensure stable and comfortable vehicular motion despite potential spacing changes.

Main Methods:

• Development of tunable triple-layered error boundaries for spacing, velocity, and acceleration.
• Integration of a Barbalat-lemma-enhanced filtering-compensating mechanism.
• Application of an adaptive approach using radial basis function neural networks (RBFNNs) for asymptotic error tracking.
• Proposal of an adaptive backstepping control integrating proactive and reactive suppression strategies.

Main Results:

• The proposed framework effectively confines propagated errors within predefined envelopes.
• Asymptotic error tracking proactively suppresses potential fluctuations in vehicle dynamics.
• The adaptive backstepping control mitigates the unquantifiable
• butterfly effect
• .

Conclusions:

• The developed control approach significantly enhances the stability and comfort of CAV platoons.
• Theoretical analysis and simulations validate the effectiveness and superiority of the proposed method.
• This work offers a robust solution for managing complex dynamics in nonlinear vehicle platoons.