Neural-network-based approach to finite-time optimal control for a class of unknown nonlinear systems

This paper proposes a novel finite-time optimal control method based on input–output data for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. In this method, the single-hidden layer feed-forward network (SLFN) with extreme learning machine (ELM) is used to construct the...

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Veröffentlicht in:	Soft computing (Berlin, Germany) Germany), 2014-08, Vol.18 (8), p.1645-1653
Hauptverfasser:	Song, Ruizhuo, Xiao, Wendong, Wei, Qinglai, Sun, Changyin
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive systems Algorithms Artificial Intelligence Artificial neural networks Computational Intelligence Control Control methods Control theory Controllers Design Dynamic programming Engineering Euclidean space Iterative algorithms Machine learning Mathematical Logic and Foundations Mechatronics Methodologies and Application Neural networks Neurons Nonlinear systems Performance indices Robotics System dynamics Time optimal control
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