| 引用本文: | 周川, 陈庆伟, 吴晓蓓, 胡维礼.不确定非线性系统的神经网络智能重构控制[J].控制理论与应用,2004,21(2):179~182.[点击复制] |
| ZHOU Chuan, CHEN Qing-wei, WU Xiao-bei, HU Wei-li.Neural network intelligent reconf igurable control for nonlinear system with uncertainty[J].Control Theory and Technology,2004,21(2):179~182.[点击复制] |
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| 不确定非线性系统的神经网络智能重构控制 |
| Neural network intelligent reconf igurable control for nonlinear system with uncertainty |
| 摘要点击 1364 全文点击 1022 投稿时间：2001-05-09 修订日期：2002-12-31 |
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| DOI编号 10.7641/j.issn.1000-8152.2004.2.006 |
| 2004,21(2):179-182 |
| 中文关键词 神经网络 重构控制 模型跟随 |
| 英文关键词 neural networks reconfigurable control model-following |
| 基金项目 国家自然科学基金项目(60174019,60034010); 清华大学智能技术与系统重点实验室基金项目; 南京理工大学科研基金项目(41245). |
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| 中文摘要 |
| 针对一类不确定非线性动态系统,提出了一种基于神经网络动态补偿的鲁棒模型跟随重构控制策略.该方法吸取了线性模型跟随方法的基本思想,通过引入神经网络在线补偿控制器,以克服系统由故障引起的未建模非线性动态的影响,从而提高模型跟随重构控制的动态性能和稳态精度;并且当系统存在模型不确定性时,其输出仍能精确地跟踪理想模型的输出.文中还给出了特定假设条件下闭环重构控制系统稳定性的严格证明.理论分析和仿真研究表明,所提的方法是有效的并可保证闭环系统具有良好的重构性能. |
| 英文摘要 |
| A new type of robust model-following reconfigurable control strategy based on the neural network compensation is presented for a class of nonlinear systems with uncertainties. By using the neural network online compensator, this method can eliminate the effect of unmodeled dynamics caused by faults, and the system output is able to accurately track the output of an ideal model even when there exist uncertainties. Stability of the closed-loop system is rigorously established under certain assumptions . Both the theoretical analysis and the computer simulation reveal that the presented scheme is effective and the closed - loop system has a good reconfiguration performance. |
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