自适应神经元非模型多变量系统解耦控制

Adaptive Neural Non-Model Decouple Control for MIMO System

根据解耦原理和神经网络的思想 ,提出一种不依赖对象模型的自适应神经元解耦方法 ,并以采用单神经元PID作为控制器的三输入三输出系统为例 ,详细分析了神经元解耦控制的学习方法 ,及在多变量系统中的工作机理。仿真结果表明 ,其构成的神经元补偿器具有很强的自学习功能和自适应解耦能力。

Based on the principle of decoupling and neuro-network, an adaptive neural non-model decoupling method is put forward in this paper. The self-learning method of neuron decoupling and its mechanism in multi-variable system are analyzed by making a three-input and three-output system for example. The result of the simulation shows its powerful self-learning and self-adaptive decouple capabilities.