摘要
讨论了整车八自由度模型并行分布补偿(PDC)控制器的设计,并求取了公共矩阵P及其对控制器稳定性的影响。基于自适应神经网络的神经网络模糊推理系统ANFIS的自学习和非线性逼近能力,提取模糊控制规则,增强了控制器对于不同路面的适应能力。在整车悬架T-S模糊动态模型的基础上,进行了Matlab软件仿真。仿真实验表明,该控制器对于悬架整体性能有所改善。
With an eight freedom semi-active suspension model, a parallel distributed compensations （PDC） controller is discussed and designed, and a public matrix P is calculated to estimate the stability of the controller. Based on the adaptive neural network, the adaptive neuro-fuzzy inference system extracted the fuzzy control rules and enhanced the adaptability to different roads. Based on full semi-active suspension dynamic T-S fuzzy model, this control arithmetic is simulated. The experiment shows the controller is effective to improve the semi-active suspension system.
出处
《计算机工程与设计》
CSCD
北大核心
2008年第20期5273-5276,共4页
Computer Engineering and Design
