多变量系统自适应静态解耦神经控制器

2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2012-10-01 DOI:10.1109/ICACI.2012.6463205

Feng Yang

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引用次数: 0

摘要

提出了一种多变量系统自适应静态解耦神经控制器。在该智能控制系统中，采用可变遗忘因子的递推最小二乘法求解多变量系统的低阶模型参数。首先对多变量系统进行静态解耦，然后在每个输入输出路径上使用神经控制器对解耦后的多变量系统进行控制。仿真试验结果表明，该方法具有良好的性能、较强的鲁棒性和自适应性。

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A neurocontroller with adaptive static state decoupling for multivariable systems

The neurocontroller with adaptive static state decoupling for multivariable systems is proposed in this paper. In this new intelligent control system, a recursive least squares method with a changeable forgetting factor is used to obtain the parameters of the low-order model of the multivariable system. The multivariable system is decoupled statically, and then the neurocontroller is used in each input-output path to control the decoupling multivariable system. The simulation test results show that good performance, strong robustness and adaptability are obtained.

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来源期刊

2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)

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