基于神经网络的非线性预测自整定PID控制

Predictive Self-tuning PID Control of Nonlinear System Based on Multiplayer Neural Networks

提出在利用前馈神经网络对非线性系统建模的基础上,对系统输出实现递推多步预测,并且结合自整定PID方法,实现非线性系统控制,神经网络在线辨识时采用学习速度较快的扩展Kalman滤波方法,仿真实验表明了该方法的有效性.

In order to control a nonlinear system, a model of recurrent multi-step prediction of the future process outputs which is constructed based on multiplayer neural network is developed and combined with a self-tuning PID controller. In the control process, an extended Kalman filter algorithm is introduced to quicken neural training. Simulation studies show the effectiveness and good performance.