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This article presents a new method for system identification based on dynamic neural networks using prior knowledge. A discrete chart is derived from a given signal flow chart. This discrete chart is implemented in a dynamic neural network model. The weights of the model correspond to physical parameters of the real system. Nonlinear parts of the signal flow chart are represented by nonlinear subparts...
Distributed round-wire windings are usually manufactured using the insertion technology. If the needle winding technology is applied instead the end windings have to be conducted in a three-layer axial arrangement. This leads to differing coil lengths and thus to a phase asymmetry which is much more distinct than the one resulting from the insertion technology. In addition, it is possible that the...
The needle winding technology is distinguished by a high degree of flexibility and automation. However, high wire tension due to the tensile winding force proves to be detrimental. Wire stress can cause an increase of the ohmic winding resistance, thus leading to a decrease of the degree of efficiency and a reduction of the continuous power of an electric machine. A closed-loop-control of the tensile...
Automotive traction drives require primarily high degrees of efficiency and high power densities. Therefore one main goal in the production of electric traction drives is the minimization of the end windings. End windings are necessary, however, they do not add to the power transformation and in addition they increase the space and the copper losses. In the serial production of distributed round-wire-windings...
The relationship between impregnation process and winding temperature has not been analyzed in detail yet. Therefore, one purpose of this paper is to investigate the correlation between impregnation process, resin absorption, applied resin, and thermal behavior. Apart from thermal behavior, it has to be ensured that the lifetime of the manufactured electrical machines still meets industrial specifications...
This paper presents a pruning algorithm using adaptive pruning interval for system identification with general dynamic neural networks (GDNN). GDNNs are artificial neural networks with internal dynamics. All layers have feedback connections with time delays to the same and to all other layers. The parameters are trained with the Levenberg-Marquardt (LM) optimization algorithm. Therefore the Jacobian...
"For original paper see O. De Jesus, .ibid., vol. 18, no. 1, p.14-27,(2007)",. In a recent paper, De Jesus proposed a general framework for describing dynamic neural networks. Gradient and Jacobian calculations were discussed based on backpropagation-through-time (BPTT) algorithm and real-time recurrent learning (RTRL). Some errors in the paper of De Jesus bring difficulties for other researchers...
This paper recapitulates the adaptive (time- varying) control strategy funnel-control (FC) and introduces its direct derivative error reference control (ERC) with specially designed Funnel boundaries and auxiliary reference. Both controller designs are comparatively applied to a nonlinear two-mass flexible servo system for speed control. ERC (as derivative of FC) is based on the high-gain controllability...
An adaptive (time-varying) MIMO/SISO control strategy - funnel-control - for position control of nonlinear, coupled (rigid) robotic systems is presented and its applicability in robotics introductory shown. The concept is based on the high-gain controllability of minimum-phase systems with relative degree one and known high-frequency gain. The approach allows prescribed transient behavior without...
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