Data-driven adaptive dynamic programming schemes for non-zero-sum games of unknown discrete-time nonlinear systems
Authors:
- He JiangHJHe Jiang
- Huaguang ZhangHZHuaguang Zhang
- Kun ZhangKZKun Zhang
- Xiaohong CuiXCXiaohong Cui
- 1 January 2018
- journal article
- research article
- Published by Elsevier in Neurocomputing
- Vol. 275, 649-658
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (61433004, 61627809, 61621004)
This publication has 62 references indexed in Scilit:
- Neural Network Based Online Simultaneous Policy Update Algorithm for Solving the HJI Equation in Nonlinear $H_{\infty}$ ControlIEEE Transactions on Neural Networks and Learning Systems, 2012
- A boundedness result for the direct heuristic dynamic programmingNeural Networks, 2012
- A three-network architecture for on-line learning and optimization based on adaptive dynamic programmingNeurocomputing, 2012
- Finite-horizon neuro-optimal tracking control for a class of discrete-time nonlinear systems using adaptive dynamic programming approachNeurocomputing, 2012
- Multi-player non-zero-sum games: Online adaptive learning solution of coupled Hamilton–Jacobi equationsAutomatica, 2011
- Online actor–critic algorithm to solve the continuous-time infinite horizon optimal control problemAutomatica, 2010
- Optimal control of unknown affine nonlinear discrete-time systems using offline-trained neural networks with proof of convergenceNeural Networks, 2009
- Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approachAutomatica, 2005
- Adaptive dynamic programmingIEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 2002
- Online learning control by association and reinforcementIEEE Transactions on Neural Networks, 2001