自调整模糊控制技术在汽车悬架系统中的应用

以车辆操纵稳定性及行驶平顺性为控制目标,提出一种在线可调整的模糊控制算法,其模糊控制规则表可以用解析方法得到.该算法不仅体现了一般模糊控制算法对非线性系统具有的明显优势,而且可以利用LMS自适应模块调整模糊控制器的修正因子,改善了一般模糊控制算法对专家先期经验依赖的缺陷.通过对简化的车辆模型仿真计算分析,证明该算法对悬架系统的振动控制具有较好的效果;并在两自由度的悬架系统试验台架上进行了试验研究,结果证明,与被动悬架系统相比,LMS自适应模糊主动悬架系统簧上质量加速度均方根降低41%.

Self-adjustment fuzzy control for vehicle suspension system

To improve the riding comfort and handling safety of a vehicle, an adjustable fuzzy control algorithm, whose fuzzy control rule table can be obtained with the numerical calculation. Because the algorithm can adjust the rectification factor of fuzzy controller with the least means squares (LMS) method, it not only reflects the advantage of fuzzy logic in a nonlinear system but also can improve the disadvantage of common fuzzy control method strongly depending on the experience. For two degrees of freedom vehicle model, the simulation of vehicle performance in single frequence signal was studied. Results show the adjustable fuzzy controller can reduce the acceleration of the sprung mass. According to the experiment of the vehicle model, the results further improve the sprung mass acceleration mean square of the LMS adaptive active suspension system, a 41% reduction from an uncontrolled suspension system.