Comparative Study between Intelligent Algorithms for Active Force Control of Side Car Mirror Vibration

摘要

Side and internal mirrors are used widely in vehicles to have better vision of road, and they play important role in driving controls. Whereas vehicles are exposed to vibration permanently due to road profile, generated vibration in mirrors produces image blurring. Thus maybe driver vision is affected by this issue and unwanted crashes are occurred. Some active vibration controllers were developed based on PID scheme, but this vibration is happen with high speed and conventional controllers cannot attenuate oscillation superiorly. Active force control (AFC) by providing extra feedback can enhance performance of controller in vibration cancelling when high speed disturbances are exciting. In this paper, AFC hybridized to iterative learning algorithm (IL) and neural network (NN). These two schemes were simulated and compared together to find best intelligent method for this purpose. Various disturbances were exerted to the systems, and accuracy and stability of controllers were reached. The results show that AFC-IL has better potential in noise termination compared to AFC-NN in car side mirror vibration reduction.