基于bp神经网络的pid自整定仿真研究

摘要：针对传统PID控制器参数调整困难、调整时间长、调整效果不理想的问题，本文提出了一种基于BP神经网络的PID自整定控制算法。该算法将传统PID控制器中的比例、积分、微分三个参数视为输入层的神经元，将PID控制器输出的控制量作为输出层的神经元，通过对训练样本的学习，使得神经网络具有良好的自适应能力，可以根据不同的控制对象及控制要求自动调整PID参数，从而实现对控制系统的自整定。通过MATLAB仿真验证，该算法具有良好的控制性能和鲁棒性，可以应用于多种控制对象的控制系统中。

关键词：BP神经网络；PID控制器；自整定；MATLAB仿真

Abstract: In view of the difficulties in parameter adjustment, long adjustment time and unsatisfactory adjustment effect of traditional PID controller, this paper proposes a PID self-tuning control algorithm based on BP neural network. In this algorithm, the three parameters of proportion, integral and derivative in the traditional PID controller are regarded as the neurons of the input layer, and the control quantity output by the PID controller is regarded as the neurons of the output layer. By learning the training samples, the neural network has good adaptability and can automatically adjust the PID parameters according to different control objects and control requirements, so as to achieve self-tuning of the control system. Through MATLAB simulation verification, the algorithm has good control performance and robustness, and can be applied to control systems of various control objects.

Keywords: BP neural network; PID controller; self-tuning; MATLAB simulation.