Study of Semiactive Adaptive Control Algorithms with Magneto-Rheological Seat Suspension

This paper presents a parametric study of two semiactive adaptive control algorithms through simulation: the non-model based skyhook control, and the newly developed model-based nonlinear adaptive vibration control. This study includes discussion of suspension model setup, dynamic analysis approach, and controller tuning. The simulation setup is from a heavy-duty truck seat suspension with a magneto-rheological (MR) damper. The dynamic analysis is performed in the time domain using sine sweep excitations without the need to linearize such a nonlinear semiactive system that is studied here. Through simulation, the effectiveness of both control algorithms is demonstrated for vibration isolation. The computation flops of the simulation in the SIMULINK environment are compared, and the adaptability is studied with respect to plant variations and different excitation profiles, both of which come across typically for vehicle suspension systems. The comparison shows that a new control approach is necessary that can take advantage of both studied control algorithms for industrial commercialization.