Robust Linear-Optimal Control Laws for Active Suspension Systems

Abstract

The stability robustness of linear-optimal control laws for quarter-car active suspension systems is evaluated using stochastic robustness analysis. Simultaneous parameters variations and neglected actuator and sensor dynamics are considered for LQ active suspension systems and for a single-measurement LQG system to determine the effects of uncertainty on system stability. The results indicate that neglected actuator and sensor dynamics have a small effect on stability robustness, while parameter uncertainty, particularly that of the “sprung mass” is of great concern. The effectiveness of Loop Transfer Recovery on active suspension systems with both parameter uncertainty and higher-order uncertainty is discerned. The analysis shows that when Loop Transfer Recovery is applied arbitrarily to uncertain systems, both estimator performance and system robustness can decrease. Nevertheless, it is concluded that the impact of the robustness recovery method is determined by stochastic stability robustness analysis, and the recovery design parameter that provides sufficient robustness with minimal performance degradation is readily identified. The effect of LQ design parameters on robustness also is considered. The paper presents robustness analysis and synthesis methods for a quarter-car model that can be applied to higher-order active suspension systems.