Fuzzy Finite Memory State Estimation for Electro-Hydraulic Active Suspension Systems

Abstract

This paper presents a novel nonlinear estimator called the fuzzy finite memory (FFM) state estimator for electro-hydraulic active suspension systems, based on fuzzy techniques and finite impulse response. The Takagi-Sugeno fuzzy model is introduced to effectively describe highly nonlinear suspension systems with electro-hydraulic actuator dynamics. Compared with the conventional state estimator, which has an infinite memory structure and requires whole data from the initial to current time, the proposed fuzzy state estimator with a finite memory structure guarantees robustness against external disturbances and modeling uncertainty. The simulation results verify that the developed fuzzy finite memory state estimator is more robust under external disturbances and modeling uncertainties than the existing infinite impulse response nonlinear estimator.

Keywords

• Half-vehicle suspension system
• state estimation
• finite memory structure
• electro-hydraulic actuator
• nonlinear systems
• T-S fuzzy model