针对工业过程中普遍存在的时滞、非线性、对象参数时变等特性，提出了一种基于最优预测的神经元模糊自整定PID控制算法。
To the widely existed characteristics of time-delay, non-linear and timevarying of parameters in the industry process, an adaptive neuron-fuzzy PID controller based on optimal prediction is presented.
针对汽车方向动力学控制存在的非线性和参数时变不确定性问题，提出了一种新的基于单神经元的汽车方向自适应pid控制算法。
In view of the nonlinearity and parameter time-varying uncertainty of vehicle dynamics, a novel algorithm, i. e. single neural adaptive PID control strategy, is propsed for vehicle direction control.
并应用有限元法对变幅杆进行了模态分析，得到了共振频率和位移节点等重要参数。
Normal modes in the pole and important characteristic parameters such as resonance frequency and position of the displacement node are obtained using the finite element method.
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