基于小波变换的磁流变悬架模糊控制算法

Wavelet-based fuzzy control algorithm for magneto-rheological(MR) suspension

运用小波变换的方法将汽车行驶时车身振动信号分解成若干频率成分,分解结果经模糊化处理后作为模糊控制器的输入,根据振动能量的频域分布和车辆悬架阻尼匹配原理制订模糊控制规则,实时调节磁流变阻尼器的阻尼力。实车道路试验表明,基于小波变换的模糊控制算法无论对车身振动还是车轴振动都取得了良好的抑制效果(共振峰值下降了5dB),并且比天棚阻尼控制更具优势。由于该算法只需要一个传感器测量车身加速度,不需要预测路面,是一种非常有应用前景的算法。

Vibration signal of automotive body is decomposed in various frequency via wavelet transform. The decomposed results are fuzzified as inputs of fuzzy controller. Control rules is selected according to frequency spectrum of vibration signal and damp matching for vehicle suspension. The force of MR damper will be adjusted for seml-active suspension by the controller in real-time. The results of road test indicate that the wavelet-based fuzzy control algorithm has good performance to reduce vibration vehicle body and axes. The resonant peak values of them have dropped 5dB. This algorithm has comparative advantage in performance than skyhook. Since the algorithm only need one sensor to measure the acceleration of vehicle body without forecasting road profile, it is one of most promising candidate for automotive applications.