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首页> 外文期刊>Circuits and systems >Single Phase Induction Motor Drive with Restrained Speed and Torque Ripples Using Neural Network Predictive Controller
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Single Phase Induction Motor Drive with Restrained Speed and Torque Ripples Using Neural Network Predictive Controller

机译：基于神经网络预测控制器的转速和转矩波动受限的单相感应电动机驱动

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摘要

In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of DC drives. Precise control of drives is the main attribute in industries to optimize the performance and to increase its production rate. In motion control, the major considerations are the torque and speed ripples. Design of controllers has become increasingly complex to such systems for better management of energy and raw materials to attain optimal performance. Meager parameter appraisal results are unsuitable, leading to unstable operation. The rapid intensification of digital computer revolutionizes to practice precise control and allows implementation of advanced control strategy to extremely multifaceted systems. To solve complex control problems, model predictive control is an authoritative scheme, which exploits an explicit model of the process to be controlled. This paper presents a predictive control strategy by a neural network predictive controller based single phase induction motor drive to minimize the speed and torque ripples. The proposed method exhibits better performance than the conventional controller and validity of the proposed method is verified by the simulation results using MATLAB software.
机译：在工业驱动器中，电动机被广泛地用于运动控制，而感应电动机由于其广泛的与直流驱动器相似的性能特征而成为目前最熟悉的驱动器。精确控制驱动器是优化性能并提高生产率的行业的主要属性。在运动控制中，主要考虑因素是转矩和速度波动。对于这样的系统，控制器的设计变得越来越复杂，以更好地管理能源和原材料以获得最佳性能。参数评估结果不理想，导致操作不稳定。数字计算机的迅速发展为实现精确控制带来了革命性变化，并允许将高级控制策略实施到极其多方面的系统中。为了解决复杂的控制问题，模型预测控制是一种权威性方案，它采用了要控制过程的显式模型。本文提出了一种基于神经网络预测控制器的预测控制策略，该控制器基于单相感应电动机驱动，以最大程度地减小速度和转矩波动。与传统控制器相比，该方法具有更好的性能，并通过MATLAB仿真结果验证了该方法的有效性。

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