引用本文: | 孙多青.多输入–多输出非线性系统的特征模型及在挠性卫星姿态控制中的应用[J].控制理论与应用,2011,28(12):1763~1772.[点击复制] |
SUN Duo-qing.Characteristic model for multi-input-multi-output nonlinear systems and its application in flexible satellite attitude control[J].Control Theory and Technology,2011,28(12):1763~1772.[点击复制] |
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多输入–多输出非线性系统的特征模型及在挠性卫星姿态控制中的应用 |
Characteristic model for multi-input-multi-output nonlinear systems and its application in flexible satellite attitude control |
摘要点击 2244 全文点击 1559 投稿时间:2010-08-28 修订日期:2011-05-11 |
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DOI编号 10.7641/j.issn.1000-8152.2011.12.CCTA100988 |
2011,28(12):1763-1772 |
中文关键词 非仿射非线性系统 特征模型 分层模糊系统 模糊控制 预测控制 卫星姿态控制 |
英文关键词 non-affine nonlinear system characteristic model hierarchical fuzzy system fuzzy control predictive control satellite attitude control |
基金项目 国家自然科学基金资助项目(60874055); 河北科技师范学院科研创新团队和重点学科建设经费资助项目(CXTD2010-05). |
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中文摘要 |
研究多输入– 多输出(MIMO)高阶非仿射非线性系统的特征建模问题. 首先证明了MIMO高阶非仿射非线性系统的特征模型可用二阶时变差分方程组描述, 并给出了特征模型的建模误差. 然后设计了基于特征模型的自适应模糊广义预测控制器, 利用Lyapunov方法分析了闭环系统的稳定性. 由于控制结构中使用了分层模糊逻辑系统, 从而极大减少了模糊规则和可调参数的个数, 提高了控制的实时性. 通过对挠性卫星姿态控制的仿真研究验证了所给控制方案的有效性, 可实现高精度的姿态控制, 且该方法具有较强的鲁棒性. |
英文摘要 |
The characteristic modeling is investigated for multi-input and multi-output higher-order non-affine nonlinear systems. First, we prove that the characteristic model for the above systems can be expressed by a system of quadratic timevarying difference equations and estimate the characteristic modeling errors. Next, we design an adaptive fuzzy generalized predictive controller based on this characteristic model, and analyze the stability of the closed-system using Lyapunov method. Because hierarchical fuzzy logic systems are employed in the control architecture, the number of fuzzy rules and adjustable parameters in a fuzzy logic controller are reduced greatly, thus improving the real-time operation performances of the control. Finally, the results from the control simulation on a flexible satellite attitude validate that the proposed control scheme is effective and has the advantages of high steady-state precision and strong robustness. |