中文摘要：

为追踪的车辆的半活跃的暂停系统的神经原比例集成(PI ) 控制策略基于它的唯一的结构和开车交通的多重、复杂的环境被建议。一个适应基因算法被用来优化神经原 PI 控制器的参数。为追踪的车辆的半活跃的暂停系统的神经原 PI 控制的模拟结果显示垂直振幅，沥青角度和车辆的垂直加速很好被控制。垂直振幅的根平均数平方(RMS ) 为沥青角度在 37.2% ，和 45.2% 减少， 38.6% 为垂直加速。为在海底的追踪的车辆模型采矿的半活跃的暂停系统的神经原 PI 控制实验的研究显示沿着垂直方向颤动的重量加速的 RMS 在 29.5% 减少，力量光谱汽车身体的加速的密度回声山峰在 23.8% 减少。

英文摘要：

A neuron proportion integration （PI） control strategy for semi-active suspension system of tracked vehicle was proposed based on its unique structure and the multiple and complex environment of the driving traffic. An adaptive genetic algorithm is used to optimize the parameters of the neuron PI controller. The simulation result of the neuron PI control for semi-active suspension system of tracked vehicle indicates that the vertical amplitude, pitch angle and vertical acceleration of the vehicle are well controlled. The root mean square （RMS） of the vertical amplitude decreases by 37.2%, and 45.2% for the pitch angle, 38.6% for the vertical acceleration. The research of neuron PI control experiment for the semi-active suspension system of the tracked vehicle model mining in benthal indicates that the RMS of the weight acceleration vibrating along the vertical direction decreases by 29.5%, the power spectral density resonance peak of the acceleration of the car body decreases by 23.8%.