Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/126687
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dc.contributor.author | Tang, D. | - |
dc.contributor.author | Chen, L. | - |
dc.contributor.author | Tian, Z.F. | - |
dc.contributor.author | Hu, E. | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Journal of Vibration and Control, 2021; 27(3-4):451-467 | - |
dc.identifier.issn | 1077-5463 | - |
dc.identifier.issn | 1741-2986 | - |
dc.identifier.uri | http://hdl.handle.net/2440/126687 | - |
dc.description | Article first published online: May 28, 2020 | - |
dc.description.abstract | This study deals with improving airfoil active flutter suppression under control-input constraints from the optimal control perspective by proposing a novel optimal neural-network control. The proposed approach uses a modified value function approximation dynamically tuned by an extended Kalman filter to solve the Hamilton–Jacobi–Bellman equality online for continuously improved optimal control to address optimality in parameter-varying nonlinear systems. Control-input constraints are integrated into the controller synthesis by introducing a generalized nonquadratic cost function for control inputs. The feasibility of using a performance index involving the nonquadratic control-input cost with the modified value function approximation is examined through the Lyapunov stability analysis. Wind tunnel experiments were conducted for controller validation, where an optimal controller synthesized offline via linear parameter-varying technique was used as a benchmark and compared. It is shown, both theoretically and experimentally, that the proposed method can effectively improve airfoil active flutter suppression under control-input constraints. | - |
dc.description.statementofresponsibility | Difan Tang, Lei Chen, Zhao F Tian and Eric Hu | - |
dc.language.iso | en | - |
dc.publisher | SAGE Publications | - |
dc.rights | © The Author(s) 2020. | - |
dc.source.uri | https://journals.sagepub.com/home/jvc | - |
dc.subject | Active control; airfoil flutter; constrained inputs; nonlinear control; neural networks; optimal control | - |
dc.title | A neural network approach for improving airfoil active flutter suppression under control-input constraints | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1177/1077546320929153 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Tang, D. [0000-0002-7143-0441] | - |
dc.identifier.orcid | Chen, L. [0000-0002-2269-2912] | - |
dc.identifier.orcid | Tian, Z.F. [0000-0001-9847-6004] | - |
dc.identifier.orcid | Hu, E. [0000-0002-7390-0961] | - |
Appears in Collections: | Aurora harvest 8 Chemical Engineering publications |
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