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The proposed controller is based on conventional vector control system supplemented by an ANN-based current decoupling network used to develop the required rotor current components based on the required grid power level and flywheel instantaneous speed.
The proposed controller is based on the feedforwad neural network.
The proposed controller is based on feedback linearization, and formation errors are guaranteed to be globally asymptotically stable.
The structure of the proposed controller is based on the T-S fuzzy systems with saturated input.
The proposed controller is based on a robust linear quadratic regulator with prescribed degree-of-stability (LQRPDS).
The proposed controller is based on a classical linear compensator, which is designed and tuned using only the well-known dynamics of the WEC.
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The proposed controllers are based on the notion of convergent systems.
The proposed controllers are based on a systematic strategy, which calculate nonlinear controllers for generating units in a power plant, both for voltage and velocity regulation.
The proposed SVC controller is based on the discrete time filtered direct control theory by which a multilayer neural network with the hyperbolic tangent activation function is derived.
The workflow of the proposed host controller is based on the initialization of the card followed by data transfer (read/write) sequences.
The proposed MPPT controller is based on fuzzy logic and operates under variable irradiance and temperature conditions.
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Justyna Jupowicz-Kozak
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