模糊神经网络在解耦控制中的研究

Application of Fuzzy Neural Network to Decoupling Control

在工业生产过程中,针对纯迟延、时变、强耦合的多输入多输出现象,提出一种基于模糊神经网络解耦和PID控制相结合,对系统进行解耦控制的方法。这种方法不需要建立多变量对象精确的数学模型,通过对大迟延大惯性强耦合的循环流化床锅炉床温-主汽压力对象进行仿真,其结果表明,解耦控制效果很好,具有良好的静态性、动态性及鲁棒性。

In the industrial production process, to the problems of the pure delay, time-variation and the strong coupling of the multiinput and multi-output phenomenon, a method is proposed that does not need to establish the precise multiple variable object mathematical model, based on the union of the fuzzy neural network decoupling and the PID control to control the decoupling of the system. The simulation result to the double-input and double-output coupling objects shows that this method has a good decoupling control performance and a great robustness.