Dynamic Modeling of Magnetorheological Damper and Force Tracking Using Particle Swarm Optimization
Keywords:
Hysteresis behavior, force tracking control, magnetorheological damper, particle swarm optimization, Spencer modelAbstract
The magnetorheological (MR) damper is the actuator that is typically and recently used to improve the semi active vehicle ride comfort. In this study, the MR damper is investigated in order to capture its hysteresis behavior using the Spencer model. The behavior of the Spencer model is evaluated and validated based on the force-velocity and force-displacement characteristics. The investigation of the MR damper system using the force tracking control (FTC) with particle swarm optimization (PSO) is also conducted to estimate the amount of voltage output produced based on the response of MR damper force and desired control force. It has been demonstrated from simulation that the MR damper system has a good hysteresis behavior of the said characteristics. Also, by implementing the FTC with PSO approach, the proposed MR damper force is able to track the desired force better than the heuristic method for up to 2.47% error considering a given desired input force.References
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