Dynamics identification and control of nonlinear MIMO coupled plant using supervised neural gas and comparison with recurrent neural controller
Author:
Funder
ECSC, The Commission of the European Communities, European Coal and Steel
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/content/pdf/10.1007/s00521-019-04195-9.pdf
Reference22 articles.
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2. Cottrell M, Hammer B, Hasenfuss A, Villmann T (2006) Batch and median neural gas. Neural Netw 19(6–7):762–771
3. Hammer B, Strickert M, Villmann T (2005) Supervised neural gas with general similarity measure. Neural Process Lett 21:21–44
4. Hammer B, Hasenfuss A, Schleif FM, Villmann T (2006) Supervised batch neural gas. In: Artificial neural networks in pattern recognition, pp 33–45
5. Narendra KS, Parthasarathy K (1990) Identification and control of dynamical systems using neural networks. IEEE Trans Neural Netw 1(1):4–27
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1. Non-linear hydraulic system (MIMO) plant for optimal control and identification by hybrid BCMO-RERNN strategy;International Journal of Heavy Vehicle Systems;2024
2. Double internal loop higher-order recurrent neural network-based adaptive control of the nonlinear dynamical system;Soft Computing;2023-03-27
3. Control of a MIMO Coupled Plant Using a Neuro-Fuzzy Adaptive System Based on Boolean Relations;IEEE Access;2021
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