Adaptive Fuzzy Output Feedback Control Design for Pneumatic Active Suspension With Unknown Dead Zone

Abstract

This study proposes an adaptive fuzzy state observer-based command filtering technique for a pneumatic active suspension considering the effects of uncertain parameters, unmeasured states, and non-ideal characteristics of the air spring actuator. Firstly, a mathematical model is constructed to investigate the dynamic behavior and examine external disturbances and system errors. The problems of input saturation and unknown dead zone are also considered in this work. By using fuzzy logic systems, unknown nonlinear functions of parametric uncertainties and various passenger masses are approximated. Then, a serial-parallel state observer is designed not only to estimate unmeasured state variables of the suspension system but also to eliminate the prediction errors of observer estimation. To enhance the suspension performance, a prescribed performance function (PPF) is applied to ensure the convergence rate of vertical displacement within specified boundaries. Besides, the “explosion of complexity” issue is eliminated by employing the command filtering technique. An adaptive fuzzy output feedback controller is then developed to reduce the tracking error of sprung mass displacement under the effect of unknown parameters, unmeasured states, and a non-ideal actuator. Moreover, the Lyapunov theorem is applied to prove the stability of the designed controller. Finally, comparative simulation examples will help verify the effectiveness and reliability of the developed approach.

Keywords

• Active suspension systems (ASSs)
• fuzzy logic systems (FLSs)
• serial-parallel observer
• prescribed performance control (PPC)
• command filtered control (CFC)