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Artificial intelligence (AI) and Biologically-inspired techniques, particularly the neural networks, are recently having significant impact on power electronics and electric drives. Neural networks have created a new and advancing frontier in power electronics, which is already a complex and multidisciplinary technology that is going through dynamic evolution in the recent years. But recently, a new...
Several methods have been introduced for identification of nonlinear processes via locally or partially linear models. Unfortunately, most of these methods have a training phase which should be done offline. There are phenomena that possess time varying behavior. Furthermore, the amount, distribution and/or quality of measurement data that is available before the model is put to operation may be insufficient...
Intelligent control of home appliances, have in recent years, attracted much theoretical attention, as well as becoming a major factor for industrial and economic success and rapid market penetration. Washing machines represent an important market. Intelligent control techniques are capable of providing useful means for both easier use and energy and water conservation. In this paper, we use two techniques...
In this paper the locally linear neurofuzzy (LLNF) models with data fusion approach are used to solve the spacecraft attitude estimation problem based on magnetometer sensors and sun sensors observations. LLNF with locally linear model tree (LoLiMoT) algorithm as an incremental learning algorithm have been used several times as a well-known method for nonlinear system identification and estimation...
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