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For: Liang Y, Zhang H, Xiao G, Jiang H. Reinforcement learning-based online adaptive controller design for a class of unknown nonlinear discrete-time systems with time delays. Neural Comput Appl 2018. [DOI: 10.1007/s00521-018-3537-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Number Cited by Other Article(s)
1
Tu Y, Fang H, Yin Y, He S. Reinforcement learning-based nonlinear tracking control system design via LDI approach with application to trolley system. Neural Comput Appl 2022. [DOI: 10.1007/s00521-021-05909-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
2
Treesatayapun C. Knowledge-based reinforcement learning controller with fuzzy-rule network: experimental validation. Neural Comput Appl 2019. [DOI: 10.1007/s00521-019-04509-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
3
Fuzzy adaptive dynamic programming-based optimal leader-following consensus for heterogeneous nonlinear multi-agent systems. Neural Comput Appl 2019. [DOI: 10.1007/s00521-019-04263-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
4
He S, Zhang M, Fang H, Liu F, Luan X, Ding Z. Reinforcement learning and adaptive optimization of a class of Markov jump systems with completely unknown dynamic information. Neural Comput Appl 2019. [DOI: 10.1007/s00521-019-04180-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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