Abstract
The photovoltaic generator exhibits a nonlinear v - i characteristic and its optimum power point varies with solar insolation. An intermediate converter is required to match the photovoltaic system to the load, and to operate the solar cell array (SCA) at an optimum point for all solar insolations. In this paper an adaptive controller is designed using an artificial neural network for optimum operation of the SCA. A controller algorithm is developed by matching the SCA to the motor load, so that the combined system can operate at optimum level. While designing the adaptive controller, solar insolation is taken as input; converter chopping is the output. The converter chopping ratios for different solar insolations are obtained from the trained neural network and are compared with computed gains. The MATLAB software is used for design and simulation purposes.
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