基于对角递归神经网络的在线自整定解耦控制算法(英文)  

Decoupling Control Algorithm of Online Self-tuning Based on DRNN

作　　者：陶平 肖超[2] 

机构地区：[1]重庆第二中级人民法院数据处理中心,重庆404020 [2]重庆大学自动化学院,重庆400044

出　　处：《机床与液压》2013年第12期123-128,共6页Machine Tool & Hydraulics

摘　　要：为了解决控制系统中一个回路参数变化导致其他回路的运行参数改变,提出了一种基于DRNN的在线自整定解耦控制算法。以某被控对象温湿度控制为例构建了数学模型,分析了系统变量之间的耦合关系,设计了解耦网络。将存在耦合关系的多变量控制系统变换为独立的单变量控制系统,以消除相关控制通道之间的影响。基于所提出的对角递归神经网络解耦算法进行了系统仿真实验。系统仿真响应显示:经过解耦后的温湿控制2个通道相互之间影响很小,实现了耦合变量的解耦。仿真研究结果表明:提出的解耦控制算法是可行与合理的。In order to solve the puzzle that the change of a loop circuit parameter results in operation parameters change of other loop circuit in the control system, the paper proposed a sort of decoupling control algorithm of online self-tuning based on DRNN. In the paper, it took the temperature and humidity control of a certain controlled object as an example, constructed the mathematic model, analyzed the coupling relationship among the system variable, designed the decoupling network. It transforms the multi-variable control system with coupling relationship as the independent single-variable control system so as to eliminate the effect among related control channels. Based on decoupling algorithm of DRNN proposed in this paper, it made the research on system simulation experiment, and the response of system simulation demonstrated that it is very small to the effect of two channels of temperature and humidity control after through decoupiing, and realized the decoupling among coupling variables. The results of simulation research show that the proposed decoupling control algorithm is feasible and reasonable.

关 键 词：自整定解耦PID控制器 对角递归神经网络 参数整定策略 温湿度解耦 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]