| 引用本文: | 石宇静,柴天佑.基于神经网络与多模型的非线性自适应广义预测解耦控制[J].控制理论与应用,2008,25(4):634~640.[点击复制] |
| SHI Yu-jing,CHAI Tian-you.Nonlinear adaptive decoupling generalized predictive control using neural networks and multiple models[J].Control Theory and Technology,2008,25(4):634~640.[点击复制] |
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| 基于神经网络与多模型的非线性自适应广义预测解耦控制 |
| Nonlinear adaptive decoupling generalized predictive control using neural networks and multiple models |
| 摘要点击 1699 全文点击 1148 投稿时间：2006-09-02 修订日期：2007-09-10 |
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| DOI编号 |
| 2008,25(4):634-640 |
| 中文关键词 非线性 广义预测控制 解耦 神经网络 多模型 |
| 英文关键词 nonlinear generalized predictive control decoupling neural networks multiple models |
| 基金项目 国家重点基础研究发展计划(973)项目(2002CB312201); 国家自然科学基金重点资助项目(60534010); 国家创新研究群体科学基金资助项目(60521003); 长江学者和创新团队发展计划资助项目(IRT0421). |
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| 中文摘要 |
| 针对一类非线性多变量离散时间动态系统, 提出了基于神经网络与多模型的非线性自适应广义预测解耦控制方法. 该控制方法由线性鲁棒广义预测解耦控制器和神经网络非线性广义预测解耦控制器以及切换机构组成.线性鲁棒广义预测解耦控制器用于保证闭环系统输入输出信号有界, 神经网络非线性广义预测解耦控制器能够改善系统性能. 切换策略通过对上述两种控制器的切换, 保证系统稳定的同时, 改善系统性能. 同时本文给出了所提自适应解耦控制方法的稳定性和收敛性分析. 最后, 通过仿真实例验证了该方法的有效性. |
| 英文摘要 |
| A nonlinear adaptive decoupling generalized predictive control approach based on neural networks and multiple models is proposed for a class of nonlinear multivariable discrete time dynamical systems. The control approach is composed of a linear robust decoupling generalized predictive controller, a neural network nonlinear decoupling generalized predictive controller and a switching mechanism. The linear robust decoupling generalized predictive controller ensures the boundedness of the input and output signals in the closed-loop system, and the neural network nonlinear decoupling generalized predictive controller improves the performance of the system. By using the switching scheme between the linear and nonlinear controllers, it is demonstrated that the stability and the improved system performance can be achieved simultaneously. Stability and convergence analysis are also given. Finally, simulation examples are presented to show the effectiveness of the proposed method. |