基于单神经元PID的车辆主动悬架最优自适应控制

为克服路面一车辆系统中存在的动态行为不确定性，针对1/4车辆主动悬架系统，设计了一个基于单神经元PID的自适应控制器，并采用二次型性能指标对控制器参数进行了优化设计。研究了系统在随机路面激励条件下的时域响应，计算了振动响应的均方根值，考察了在变参数条件下控制器的鲁棒特性。仿真结果表明，该控制器能有效改善车辆的综合性能，尤其是平顺性和舒适性，且鲁棒性好，对模型参数的变化具有一定的适应性，便于实现和应用。

Optimal Adaptive Control for Vehicle Active Suspension Based on Single Neuron PID

In order to overcome the uncertainties of the dynamic behavior of road-vehicle systems, an adaptive controller based on single neuron PID was designed. Then the neuron PID controller was applied to carry out adaptive control of a quarter vehicle active suspension. The optimum parameters of the controller were obtained by means of minimization of the quadratic performance index. The responses of vehicle in time domain were simulated in stochastic road excitation and the RMS(root mean squre) values of their responses were also calculated. The robustness of the controller was investigated in various vehicle parameters. The simulation results show that the proposed controller can effectively improve the overall performance of vehicle, especially in ride comfort. It can also achieve a good robustness and adaptability against model parameter uncertainties, and is convenient to realize.