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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Deb, D. Sonowal, S. |
| Copyright Year | 2013 |
| Description | Author affiliation: Sch. of Electr. Eng. & Comput. Sci., Seoul Nat. Univ., Seoul, South Korea (Sonowal, S.) |
| Abstract | This paper presents a neural network-based adaptive compensation scheme to cancel the effect of uncertain, highly complex and dynamic synthetic jet actuator nonlinearities. Approximation of a nonlinearly parameterized model of synthetic jet actuator characteristics by a linearly parameterized function is performed using neural network approximators. The nonlinearity function is approximated over a range of rotor rotational speed of a wind turbine blade. An adaptive inverse is employed for cancelling the effect of actuator nonlinearities, which is accomplished by use if another neural network. Adaptive update laws are also employed for estimation of blade physical dimensional parameters. A state feedback control law is designed to control the nonlinear wind turbine dynamics in presence of signal dependent actuator nonlinearities. |
| Starting Page | 152 |
| Ending Page | 157 |
| File Size | 268135 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479915590 |
| ISSN | 10851992 |
| DOI | 10.1109/CCA.2013.6662759 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-08-28 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Actuators Wind turbines Approximation methods Blades Adaptive systems Neural networks Rotors synthetic jet actuators Actuator nonlinearity adaptive compensation wind turbine control neural networks |
| Content Type | Text |
| Resource Type | Article |
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