基于粒子群改进神经网络的USM智能控制

Shenglin Mu, Kanya Tanaka, Shota Nakashima, Hiromasa Tomimoto, Shingo Aramaki
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引用次数: 2

摘要

随着老龄化社会问题的日益严重,不仅在日本,而且在世界范围内,社会和福利领域越来越受到关注。近年来开展了许多老年人科技研究。在这样的背景下,对具有新颖特性的技术有很多的改进需求。介绍了一种具有吸引人特点的超声电机作动器控制方法。在医疗和福利领域,由于USMs的特殊性,预计将发挥更大的作用。本文提出了一种基于神经网络(NN)和粒子群算法(PSO)的智能PID控制方法。该方法在变增益PID控制的基础上,利用神经网络设计了智能控制器。神经网络单元的学习由粒子群算法实现。该方法可实时调节PID控制的增益。实验结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent control of USM using a modified NN with PSO
As aging society problem goes severe In not only Japan but also the whole world, more and more attentions are attracted to the social and welfare fields. Many researches on science and technology for elders are implemented in rencent years. With the background, there are a lot of needs for techonologies with novel features for improvement. In this paper, a control method with attractive features for the actuator of Ultrasonic Motors (USMs) is introduced. In medical and welfare areas, the USMs are expected to play more important roles owing to their special characteristics. In this research, an intelligent PID control method using Neural Network (NN) combined with type Particle Swarm Optimization (PSO) is developed for the control of USM. In the method, the intelligent controller is designed based on variable gain type PID control using NN. The learning of the NN unit is implemented by the PSO. The gains of PID control are adjusted by the proposed method in real-time. The effectiveness of the method is verified by experimental results.
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