Enhancing optimal controllers via techniques from robust and adaptive control
Enhancing optimal controllers via techniques from robust and adaptive control
复制标题
通过鲁棒和自适应控制技术增强最优控制器
DOI：
10.1109/cdc.1991.261797
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发表时间：
1991
期刊：
影响因子：
--
通讯作者：
J.B. Moore
中科院分区：
文献类型：
--
作者：
J. Imae;L. Irlicht;G. Obinata;J.B. Moore
提出了一种提高最优控制律鲁棒性的一般框架，重点讨论了非线性情况。该框架允许混合离线非线性最优控制，在线线性鲁棒反馈控制的最优轨迹的调节，和在线自适应技术，以提高性能/鲁棒性。对于非线性对象和线性鲁棒控制器的情形，给出了一些一般的基本稳定性性质。基于平均分析的未建模线性动态的存在下的性能增强的结果。基于平均理论的收敛性分析原则上对任何特定的非线性系统都是可能的。某些模型参考自适应控制算法作为特例出现。一个非线性最优控制问题进行了研究，以说明该技术的有效性，并指出进一步提高性能的可能性的基础上功能学习。<<ETX>>
A general framework to enhance the robustness of an optimal control law is presented, with emphasis on the nonlinear case. The framework allows a blending of offline nonlinear optimal control, online linear robust feedback control for regulation about the optimal trajectory, and online adaptive techniques to enhance performance/robustness. Some general fundamental stability properties are developed for the nonlinear plant and linear robust controller case. Performance enhancement results in the presence of unmodeled linear dynamics based on an averaging analysis. A convergence analysis based on averaging theory appears possible in principle for any specific nonlinear system. Certain model-reference adaptive control algorithms come out as special cases. A nonlinear optimal control problem is studied to illustrate the efficacy of the techniques, and the possibility of further performance enhancement based on functional learning is noted.<<ETX>>