Computational adaptive optimal control for continuous-time linear systems with completely unknown dynamics
Computational adaptive optimal control for continuous-time linear systems with completely unknown dynamics
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DOI：
10.1016/j.automatica.2012.06.096
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发表时间：
2012-10-01
期刊：
影响因子：
6.4
通讯作者：
Jiang, Zhong-Ping
中科院分区：
文献类型：
--
作者：
Jiang, Yu;Jiang, Zhong-Ping
针对具有完全未知系统动态的连续时间线性系统，提出了一种在线自适应最优控制器的策略迭代方法。该方法采用近似/自适应动态规划技术，利用状态和输入的在线信息迭代求解代数Riccati方程，而不需要系统矩阵的先验知识。此外，所有迭代都可以通过在某些固定时间间隔上重复使用相同的状态和输入信息来进行。本文提出了一种实用的在线算法，并将其应用于废气再循环增压柴油机的控制器设计。最后，对未来工作的几个方面进行了讨论。(C)2012爱思唯尔有限公司。保留所有权利。
This paper presents a novel policy iteration approach for finding online adaptive optimal controllers for continuous-time linear systems with completely unknown system dynamics. The proposed approach employs the approximate/adaptive dynamic programming technique to iteratively solve the algebraic Riccati equation using the online information of state and input, without requiring the a priori knowledge of the system matrices. In addition, all iterations can be conducted by using repeatedly the same state and input information on some fixed time intervals. A practical online algorithm is developed in this paper, and is applied to the controller design for a turbocharged diesel engine with exhaust gas recirculation. Finally, several aspects of future work are discussed. (C) 2012 Elsevier Ltd. All rights reserved.