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In this paper, we address the problem of output tracking for single-input and single-output (SISO) parametric strict-feedback (PSF) nonlinear systems in the presence of uncertain parameters under sampled-data control. We firstly develop a constructive design procedure for sampled-data controller by combining the backstepping technique with two kinds of discretization approaches. In sequel, we provide...
Many approaches to image classification tend to transform an image into an unstructured set of numeric feature vectors obtained globally and/or locally, and as a result lose important relational information between regions. In order to encode the geometric relationships between image regions, we propose a variety of structural image representations that are not specialised for any particular image...
Transfer learning aims to improve a targeted learning task using other related auxiliary learning tasks and data. Most current transfer-learning methods focus on scenarios where the auxiliary and the target learning tasks are very similar: either (some of) the auxiliary data can be directly used as training examples for the target task or the auxiliary and the target data share the same representation...
This paper presents a scalar sign function based anti-windup control method for the sampled-data system with input saturation. It is found that input saturation can be effectively approximated by the smooth scalar sign function. When saturation encounters, an iteration procedure is executed in which the weighting matrices are systematically adjusted in the LQR performance index until the obtained...
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