Approximation-free finite-time control for uncertain active suspensions with unknown time-varying input delays

Area of Science:

• Control Systems Engineering
• Automotive Engineering
• Nonlinear Dynamics

Background:

• Active suspension systems (ASSs) face challenges from uncertain nonlinearities and unknown time-varying input delays (UTIDs).
• Existing control methods may require complex models or approximations, limiting practical application.
• Enhancing transient performance and robustness in ASSs remains a key research area.

Purpose of the Study:

• To develop a novel approximation-free finite-time control method for ASSs.
• To address uncertain nonlinearities and unknown time-varying input delays (UTIDs) in ASSs.
• To improve the transient performance and overall effectiveness of active suspension systems.

Main Methods:

• Design of a finite-time prescribed performance function (FPPF) for bounded suspension motion convergence.
• Development of a novel compensator to mitigate the effects of unknown input delays.
• Implementation of an approximation-free control strategy utilizing the FPPF and compensator, avoiding neural networks and fuzzy logic.

Main Results:

• The proposed method achieves finite-time prescribed performance convergence of suspension motion despite uncertainties and UTIDs.
• Simulation results demonstrate the effectiveness of the approximation-free control strategy.
• Significant improvements in active suspension system performance were observed.

Conclusions:

• The developed approximation-free finite-time control method offers a robust solution for uncertain active suspension systems with input delays.
• The approach successfully enhances suspension performance without relying on complex approximation techniques.
• Validated through dynamic simulation, the method presents a promising advancement in automotive control systems.