In this investigation a vector controlled control characteristics of salient pole PMSM can be permanent magnet synchronous motor (PMSM) is found in [10]. Power capability of salient pole PMSMs simulated and then a wavenet (a neural network based on in variable speed drive applications has been proposed wavelet functions) based speed controller is designed to in [11]. Performance of current controllers for VSI-fed make the system more robust against parameter interior PMSM drive has been presented in [12]. Speed variations. The data for training the network is extracted from a process with several PID controllers to achieve a ontrol oin P e fo r theeflux akeing reasonable performance in all operating regions. At the operation can be found in [13]. Recently, artificial first resolution of training, the desired accuracy is neural networks have been used in system control and obtained and finds out that going to higher resolution is modeling [14]. In high performance PMSM, artificial not necessary. After determining the number of nodes at neural networks play a key role in system identification each resolution and the number of wavelets at each node, and speed control [15]. Comparative analysis of the location of nodes at each resolution is determined.intelligent controllers for high performance interior Finally on the basis of advantages of wavenets the final magnet synchronous motor drive system has been results are presented. The response of the controller proposed in [16]. El-Sousy [17] has proposed a high proves the validity of the proposed method. performance neural network model following speed controller for vector Controlled PMSM drive system.
It is well known that joint pilot and data power control, often known as JPDPC, has a significant effect on cell-free massive multiple-input multiple-output (CFmMIMO) system performance. In this paper, the uplink performance of the CFmMIMO system is evaluated under two conflicting optimization objectives (sum spectral efficiency and proportional fairness) by considering JPDPC as an optimization variable. In the CFmMIMO system with imperfect channel state information (CSI), we first formulate a multi-objective optimization (MOO) problem that can handle the fairness sum-SE trade-off problems. Then, taking into account a total energy budget for each access point, we propose a power control approach that optimally allocates power between data symbols and pilot symbols. Due to the fact that the problem is non-convex, new algorithms based on a combination of successive convex approximation and geometric programming are used to handle it. The numerical results demonstrate the benefit of optimizing the power control over both the pilot and data powers, as contrasted to the scenarios of employing full power and simply optimizing the data powers, as was done in prior studies. Furthermore, the advantage of optimal joint power control in the low SNR regime is confirmed and demonstrated to be significant.
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