-
摘要: 对于普遍存在的具有未知参数的随机最优控制问题，本文提出了一种具有学习特点的控制器设计算法.该算法用Kalman滤波估计系统的未知参数，在滚动优化机制下用动态规划获取控制增益，为了赋予控制器的学习特点，在LQG控制律中附加使下一时刻估计方差最小的学习控制分量.仿真结果表明了算法的有效性.Abstract: A new controller design algorithm with learning characteristic is proposed for the ubiquitous stochastic optimal control problem with unknown parameters. This algorithm estimates system unknown parameters by Kalman filter and obtains control gains by dynamic programming and continuous rolling optimization mechanism. In order to endow the controller with learning characteristics a learning control component which minimizes next moment estimated variance is attached to the LQG control law. Simulation results show the effectiveness of the algorithm.
-
Key words:
- Adaptive control /
- uncertainty systems /
- LQG problem /
- Kalman filter
1) 本文责任编委 方海涛 -
[1] Huang M, Wang X, Wang Z L. Multiple model adaptive control for a class of linear-bounded nonlinear systems. IEEE Transactions on Automatic Control, 2015, 60 (1):271-276 doi: 10.1109/TAC.2014.2323161 [2] Ma Y J, Jiang B, Tao G, Cheng Y H. Uncertainty decomposition-based fault-tolerant adaptive control of flexible spacecraft. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51 (2):1053-1068 doi: 10.1109/TAES.2014.130032 [3] De Villiers J P, Laskey K, Jousselme A L, Blasch E, Pavlin G, Costa P. Uncertainty representation, quantification and evaluation for data and information fusion. In:Proceedings of the 18th International Conference on Information Fusion. Washington, DC, USA:IEEE, 2015. 50-57 [4] Bellman R, Kalaba R. Dynamic Programming and Modern Control Theory. New York:Academic Press, 1965. [5] Apkarian P, Dao M N, Noll D. Parametric robust structured control design. IEEE Transactions on Automatic Control, 2015, 60 (7):1857-1869 doi: 10.1109/TAC.2015.2396644 [6] Wen J T, Kreutz-Delgado K, Bayard D S. Lyapunov function-based control laws for revolute robot arms:tracking control, robustness, and adaptive control. IEEE Transactions on Automatic Control, 1992, 37 (2):231-237 doi: 10.1109/9.121624 [7] Cao S P, Qian F C, Wang X M. Exact optimal solution for a class of dual control problems. International Journal of Systems Science, 2016, 47 (9):2078-2087 doi: 10.1080/00207721.2014.973469 [8] Qian F C, Huang J R, Liu D, Hu S L. Adaptive dual control of discrete-time LQG problems with unknown-but-bounded parameter. Asian Journal of Control, 2015, 17 (3):942-951 doi: 10.1002/asjc.v17.3 [9] Bar-Shalom Y, Wall K D. Dual adaptive control and uncertainty effects in macroeconomic systems optimization. Automatica, 1980, 16 (2):147-156 doi: 10.1016/0005-1098(80)90050-3 [10] Filatov N M. Adaptive Dual Control Theory and Applications. Berlin Heidelberg:Springer, 2004. [11] Li D, Qian F C, Fu P L. Variance minimization approach for a class of dual control problems. In:Proceedings of the 2002 American Control Conference. Anchorage, AK, USA:IEEE, 2002. 3759-3764 [12] Li D, Fu P L, Qian F C. Optimal nominal dual control for discrete-time LQG problem with unknown parameters. In:Proceedings of the 2003 SICE Annual Conference. Fukui, Japan:IEEE, 2003. 476-479 [13] Qian F C, Gao J J, Li D. Complete statistical characterization of discrete-time LQG and cumulant control. IEEE Transactions on Automatic Control, 2012, 57 (8):2110-2115 doi: 10.1109/TAC.2011.2179844 [14] Milito R, Padilla C, Padilla R, Cadorin D. An innovations approach to dual control. IEEE Transactions on Automatic Control, 1982, 27 (1):132-137 doi: 10.1109/TAC.1982.1102863 -
下载:
图(3) / 表(1)
计量
- 文章访问数: 2125
- HTML全文浏览量: 369
- PDF下载量: 952
- 被引次数: 0
