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In this paper the problem of optimizing the output regulation of a weakly dual redundant plant is addressed. When the system is under-actuated, only a subset of the outputs can be arbitrarily controlled, and the remaining ones are constrained. We investigate the problem of finding the input that minimize a cost function of the overall output tracking error, and how such solution is related to the inputs associated to the singularly optimal regulation of each output. Some interesting properties are revealed, such as the optimal solution being always included in the convex hull of singularly optimal controls and the existence of neutral reference spaces

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This paper introduces a complete work-flow for the translation of dynamic isolated signs based on data acquired from a data-glove. A sign language translation system based on a wearable device represents indeed a more efficient solution with respect to cameras or position trackers for helping speech-impaired people on a daily basis. The paper describes the different steps required for a sign language translation, namely segmentation, feature extraction and classification, together with the custom data-glove used for data-acquisition. The paper presents also experimental results, comparing different machine learning classifiers and discussing their performances both in terms of translation accuracy and computational time. The proposed work-flow has been tested both on data acquired from a custom data-glove and on a public database, and it outperforms those of other works in literature. The reported analysis suggests a multi-layer perceptron neural network as the most suitable classifier for the realization of a wearable sign language translation system.