In order to investigate and decide that the vehicle asymptotic vibration stability and improved comfort, the present paper deals with a fuzzy neural network (NN) evolved bat algorithm (EBA) backstepping adaptive controller based on grey signal predictors. The Lyapunov theory and backstepping method is utilized to appraise the math nonlinearity in the active vehicle suspension as well as acquire the final simulation control law in order to track the suitable signal. The Discrete Grey Model DGM (2,1) have been thus used to acquire prospect movement of the suspension system, so that the command controller can prove the convergence and the stability of the entire formula through the Lyapunov-like lemma. The controller overspreads the application range of mechanical elastic vehicle wheel (MEVW) as well as lays a favorable theoretic foundation in adapting to new wheels.

中文翻译：

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基于李雅普诺夫理论的主动车辆悬架系统的灰色信号预测器和模糊控制

为了研究和确定车辆渐近振动稳定性和提高舒适性，本文研究了一种基于灰色信号预测器的模糊神经网络（NN）进化蝙蝠算法（EBA）反步自适应控制器。利用李雅普诺夫理论和反步法对车辆主动悬架中的数学非线性进行评价，获得最终的仿真控制律，以跟踪合适的信号。离散灰色模型DGM(2,1)因此被用于获取悬架系统的前景运动，使得命令控制器可以通过类Lyapunov引理证明整个公式的收敛性和稳定性。