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Working robots may encounter and interact with various objects, whose dynamical characteristics are unknown; linear or nonlinear and their strength of stiffness. The interaction includes such processes as collision of arm with environments, hand gripping of objects, holding human body in medical case etc. These processes consist of free motion before touching the objects, and constrained motion after...
The article presents new way of learning, determining suitable Takagi-Sugeno (TS) fuzzy-neural network structure for modeling nonlinear process. The whole structure consists of the NARX models (Nonlinear Auto-Regressive model with eXogenous input) set. Offered algorithm uses for learning in its action cluster method to determine initial divisions of the input space. Then, according to this algorithm...
Semi-parametric regression model prediction method based on empirical mode decomposition was studied in this paper. Firstly, basic idea of the empirical mode decomposition was introduced, and the improved algorithm was proposed to mitigate the end effect in the iterative shift process. Secondly, least squares method was employed to estimate the parameter β based on the trend component of empirical...
Equipment and facility are the important basis of the production for the manufactory. Equipment possession quantity is the reasonable manufactory equipment amount that meets the production demand. The relationship among equipment possession quantity, the ratio of equipment in good condition and equipment quantity on duty is introduced, and mathematics models of equipment possession quantity is described...
OFDM model-based channel estimation techniques conventionally apply the least squares method to estimate parameters in a regression model through uniformly distributed pilots in a local region. However, the model estimation must use as many pilots as possible to reduce the effect of noises with the penalty of increasing the storage size for received OFDM symbols. We observed that the model parameters...
In this paper, the experimental results obtained in the design and implementation of a self-tunning voltage controller for a micro energy system are analyzed. Two types of indirect adaptive self-tuning schemes are proposed. Both uses a recursive estimation scheme based on the well known Least Squares method. The difference between them is the controller formulation methodology: one uses the pole placement...
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