期刊
INFORMATION SCIENCES
卷 220, 期 -, 页码 331-342出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2012.07.006
关键词
Adaptive dynamic programming; Approximate dynamic programming; Control constraints; Globalized dual heuristic programming; Neural networks; Optimal control
资金
- National Natural Science Foundation of China [60904037, 60921061, 61034002]
- Beijing Natural Science Foundation [4102061]
- China Postdoctoral Science Foundation [201104162]
In this paper, the adaptive dynamic programming (ADP) approach is employed for designing an optimal controller of unknown discrete-time nonlinear systems with control constraints. A neural network is constructed for identifying the unknown dynamical system with stability proof. Then, the iterative ADP algorithm is developed to solve the optimal control problem with convergence analysis. Two other neural networks are introduced for approximating the cost function and its derivatives and the control law, under the framework of globalized dual heuristic programming technique. Furthermore, two simulation examples are included to verify the theoretical results. (C) 2012 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据