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- W2914897401 abstract "In this paper, we present a novel active fault-adaptive control (FAC) methodology for wind turbines, which minimizes the economic cost of turbines by achieving two broad objectives: power maximization and fatigue reduction possibly under the effect of bias faults in converters. The proposed FAC system is composed of two modules: a fault diagnosis subsystem and controller redesign subsystem. The latter module is synthesized using a model-predictive control (MPC) scheme in which the constraints set of the decision variables is not naturally convex. A major contribution of the paper is the reformulation of the non-convex optimization problem into a convex problem through some new decision variables. The fault diagnosis algorithm is built upon an unknown-input-residual generator and a specifically designed filter which extracts the complete information of the fault. This fault information is subsequently used to update in real-time the constraints of the MPC thereby ensuring automatic adaptation of the control law to the new operating mode. The effectiveness of the developed scheme is demonstrated on a $2MW$ wind turbine system." @default.
- W2914897401 created "2019-02-21" @default.
- W2914897401 creator A5010806251 @default.
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- W2914897401 date "2018-12-01" @default.
- W2914897401 modified "2023-10-09" @default.
- W2914897401 title "eMPC Based Fault-Adaptive Control for Wind Turbine Converters* This research work is supported by SERB, Government of India under grant agreement no. ECR/2016/001025." @default.
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- W2914897401 doi "https://doi.org/10.1109/cdc.2018.8619190" @default.
- W2914897401 hasPublicationYear "2018" @default.
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