基于改进的通用学习算法非线性预测控制系统设计

Prediction of Design and Realization of Control System Based on Improved BP Algorithm for Nonlinear

传统的PID控制由于对象的非线性,会导致控制系统震荡加剧,而且会造成闭环系统的不稳定,这对于系统的设计与维护造成了很大的困难;为了解决该问题,提出了一种改进的ULN预估非线性预测控制系统设计方案;利用通用学习算法对不同的滞后对象进行训练,在基于对象充分学习的基础上,设计了ULN预估控制器;最后做了多组对比实验,以典型的PH中和控制系统为例,利用通用学习算法对不同的滞后对象进行训练,在基于对象充分学习的基础上,设计了ULN预估控制器;通过仿真实验结果表明,提出的方法比传统的方法具有更好地控制效果,系统具有更强的鲁棒性能。

the traditional PID control because of the nonlinear control system, will lead to increased concussion, and will cause the instability of the closed-loop system, the system design and maintenance caused great difficulties. In order to solve this problem, proposed the predictive control system design of an improved BP algorithm for nonlinear. Training of different lag object using BP neural network algorithm, based on learning object based on the design of the ULN controller. This paper makes several groups of experiments, the simulation results show that, this method has better control effect than the traditional method, the robust performance of the system more.