Interval Lower Singleton Fuzzy Optimal Controller Design of Magnetorheological Seat Suspension Integrated with Semi-Active Vehicle Suspension System

In this paper, semi-active MR main suspension system based on system controller design to minimize pitch motion linked with MR-controlled seat suspension by considering driver’s biodynamics is investigated. According to a fixed footprint tire model, the transmitted tire force is determined. The linear-quadratic Gaussian (LQG) system controller is able to enhance ride comfort by adjusting damping forces based on an evaluation of body vibration from the dynamic responses. The controlled damping forces are tracked by the signum function controllers to evaluate the supply voltages for the front and rear MR dampers. Based on the sprung mass acceleration level and its derivative as the inputs, the optimal type-2 (T-2) fuzzy seat system controller is designed to regulate the controlled seat MR damper force. The best rate for each linguistic variable is acquired by modifying the range between upper and lower membership functions (MFs), which enables accurate tracking of the seat-damping force. The parameters of the LQG main system controller and the ideal scaling lower ranges of the T-2 fuzzy seat system controller are both explored by a genetic algorithm (GA). The performance of LQG regulated for MR dampers is compared with that of linear-quadratic regulator (LQR) controlled for MR dampers and passive systems to measure the suspension efficacy under bump and random road disturbance. To verify the efficiency of the recommended integrated models on both the main and seat systems, the performance of the proposed ideal T-2 fuzzy-controlled MR semi-active seat suspension is compared with the passive seat suspension. The simulation results show that the LQG controlled connected with the T-2 fuzzy controlled can greatly improve both ride comfort and vehicle stability, among all examined systems.