首先提出基于自适应神经元的振动智能ＰＩＤ控制策略及相应高效算法，然后通过数字仿真与模型实验验证了这种算法的有效性。这种方法具有控制器参数少、结构简单、算法收敛速度快、便于实时控制等优点。与传统ＰＩＤ控制相比，控制器参数整定可通过神经网络的自组织来实现。数字仿真与实验结果表明这种方法能够有效地控制动态特性未知、所受干扰不可测的黑箱振动系统的任意振动 At first, the intelligent PID control strategy based on adaptive neuron and the corresponding efficient algorithm are proposed. Then the validity of this algorithm is verified by digital simulation and model experiment. This method has the advantages of less controller parameters, simple structure, fast algorithm convergence and convenient real-time control. Compared with the traditional PID control, controller parameter tuning can be achieved through the neural network self-organization. The numerical simulation and experimental results show that this method can effectively control the arbitrary vibration of the black box vibration system with unknown dynamic characteristics and unperturbed disturbance