一类非线性离散时间系统的神经网络解耦策略
A Neural Network Decoupling Strategy for a Class of Nonlinear Discrete Time Systems
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摘要: 考虑用神经网络作为补偿器,对一类非线性系统进行输入输出解耦.给出了这类系 统的可解耦的充要条件,并证明在该条件下系统可解耦成线性系统且极点可任意配置.基于 此,给出了这类系统的一个神经网络解耦方法.Abstract: A neural network is considered to be used as a compensator for input-output decoupling of a class of nonlinear discrete time systems. A necessary and sufficient condition for the solvability of the decoupling problem for the class of discrete time systems is given. It is also shown that if the decouling problem is solvable, the modified systems can be linear and the poles of the modified systems can be freely assigned. Based on this result, a strategy for realizing decoupling via neural networks is proposed. Simulation results supports our theory and the decoupling strategy proposed in this paper.
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Key words:
- Neural network /
- compensator /
- decoupling /
- pole placement /
- nonlinear discrete time systems
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