Adaptive Estimation and Control of Nonlinear Suspension Systems With Natural Logarithm Sliding Mode Control

This article presents an adaptive logarithm-based sliding mode control (ALSMC) for an active suspension system to enhance ride comfort while maintaining the road holding and suspension space limits. The main objective of the control design is to devise a controller that does not require precise and accurate model parameters while ensuring resilience to model uncertainty and external disturbance. To achieve this objective, a natural logarithm sliding mode control (lnSMC) approach is adopted. Unlike the conventional sliding mode control that utilizes a linear sliding surface, the lnSMC is designed based on a natural logarithmic function, which creates the boundary layer of the controlled states. Thus, the selection of the controller parameter will be more practical as its value is dependent on the desired amplitude of the controlled state. This prevents trial and error when determining the controller parameter. In this study, the system’s dynamics are represented by a nonlinear quarter-car suspension model (e.g., nonlinear springs and piecewise dampers) with unknown model parameters. An adaptive law is incorporated to estimate all unknown model parameters, which is subsequently used for updating the control law. A simulation study is carried out to illustrate the effectiveness of the proposed control law under various types of disturbances, including sinusoidal road profile, bump road profile, and random road profile disturbance.