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This paper describes a design procedure for a cascaded control system of induction motors based on compact genetic algorithms (cGAs). CGAs are search methods that process a probability vector (describing the distribution of a hypothetical population) with update rules inspired to the typical selection and recombination operations of a GA. The cGAs well lend themselves to real-time implementations...
This paper describes the implementation of a self-optimizing embedded control scheme for an induction motor drive. The online design problem is formulated as a search problem and solved with a stochastic optimization algorithm. The objective function aggregates several performance indices on tracking error and control signals, and is measured directly on the hardware bench. The online optimization...
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