Direct heuristic dynamic programming based on an improved PID neural network

In this paper, an improved PID-neural network （IPIDNN） structure is proposed and applied to the critic and action networks of direct heuristic dynamic programming （DHDP）. As one of online learning algorithm of approximate dynamic programming （ADP）, DHDP has demonstrated its applicability to large st...

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Veröffentlicht in:	Journal of control theory and applications Jg. 10; H. 4; S. 497 - 503
Hauptverfasser:	Sun, Jian, Liu, Feng, Si, Jennie, Mei, Shengwei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Heidelberg South China University of Technology and Academy of Mathematics and Systems Science, CAS 01.11.2012 Department of Electrical Engineering, Tsinghua University, Beijing 100084, China%Department of Electrical Engineering, Arizona State University, Tempe AZ 85287-5706, USA
Schlagworte:	Algorithms Brief Paper Complexity Computational Intelligence Control Control and Systems Theory Control systems Dynamic programming Engineering Heuristic Learning Mathematical analysis Mechatronics Networks Neural networks Optimization PID神经网络 Robotics Systems Theory 启发式动态规划在线学习算法基础最优性方程状态反馈系统验证输出反馈控制 Approximate dynamic programming (ADP) Direct heuristic dynamic programming (DHDP) Improved PID neural network (IPIDNN)
ISSN:	1672-6340, 1993-0623
Online-Zugang:	Volltext
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