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Unlike traditional control laws that usually require measurements with respect to a global coordinate frame and communications between a centralized operation center and agents, this book provides control laws that require only relative measurements and communications between agents without interaction with a centralized operator.
Shows the reader how to use robust iterative learning control in the face of model uncertaintyHelps to improve the performance of repetitive electromechanical tasks, widespread in industryProvides a rounded and self-contained approach to the subject of iterative learning control not available elsewhere
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